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The industrial emission of chlorinated volatile organic compounds (Cl-VOCs) is a serious environmental hazard and creates significant health risks for humans. The physicochemical methods currently applied for removing Cl-VOCs are unsustainable due to high cost, inherent complexity, and formation of secondary toxic metabolites. For several decades, biological treatment of wastes has been considered the panacea. In this light, it seems promising to extend the application of bioremediation to treat Cl-VOCs. The current review provides a comprehensive update on the use of bioreactors such as biofilters, biotrickling filters, rotating biological contactors, scrubbers, and membrane bioreactors for the remediation of Cl-VOCs-laden industrial fumes. The integration of physicochemical processes with bioreactors would aid in overcoming the limitations of any individual process and enhance the degradation rate while ensuring the long-term stability of the system. As microbes play a pivotal role in bioreactor systems, various species involved in the remediation of Cl-VOCs are discussed. The diversity of the microbes influences the stability and functioning of the community, which necessitates the incorporation of bacteria and fungi, even algae, rotifers, and nematodes in the bioreactors. The review concludes with suggestions for future research considering the current challenges in realizing the full potential of bioreactors for treating Cl-VOCs. Graphical Abstract

A large amount of wastewater is directly discharged into water bodies without treatment, causing surface water contamination. A rotating biological contactor (RBC) is an attached biological wastewater treatment process that offers a low energy footprint. However, its unstable removal efficiency makes it less popular. This study optimized operating parameters in RBC combined with external membrane filtration (RBC-ME), in which the latter acted as a post-treatment step to stabilize the biological performance. Response surface methodology (RSM) was employed to optimize the biological and filtration performance by exploiting three parameters, namely disk rotation, hydraulic retention time (HRT), and sludge retention time (SRT). Results show that the RBC-ME exhibited superior biological treatment capacity and higher effluent quality compared to stand-alone RBC. It attained 87.9 ± 3.2% of chemical oxygen demand, 45.2 ± 0.7% total nitrogen, 97.9 ± 0.1% turbidity, and 98.9 ± 1.1% ammonia removals. The RSM showed a good agreement between the model and the experimental data. The maximum permeability of 144.6 L/m2 h bar could be achieved under the optimum parameters of 36.1 rpm disk rotation, 18 h HRT, and 14.9 d SRT. This work demonstrated the effective use of statistical modeling to enhance RBC-ME system performance to obtain a sustainable and energy-efficient condition.

Effective treatment of domestic wastewater requires biological processes capable of maintaining stable performance under varying operational conditions. This study applies artificial neural network (ANN) and Gaussian process regression (GPR) to model and predict multipollutant removal performance in a lab‐scale rotating biological contactor (RBC). The RBC performance was evaluated for the removal of chemical oxygen demand (COD), ammonium‐N, and turbidity under different hydraulic retention time (HRT), sludge retention time (SRT), and disk rotational speed. ANN model demonstrated strong predictive agreement with experimental observations, effectively capturing nonlinear relationships between operational parameters and removal efficiencies. GPR provided accurate predictions together with quantitative uncertainty estimates, offering additional insight into model confidence and sensitivity across operating parameters. The combined ANN–GPR framework highlights the trade‐off between predictive accuracy and uncertainty‐aware interpretation in data‐driven modeling of the RBC bioreactor. The findings enhance understanding of parameter interactions in RBC and support the use of machine learning–based tools for performance analysis and decision support for wastewater treatment.

In this research a bench scale rotating biological contactor (RBC) was designed and constructed to produce BC. The effects of variables including rotation speed of the disk, distance between disks, disk type and external aeration on BC productivity were investigated. Results showed that the highest weight of BC produced on the surface of integrated polyethylene discs which rotated at 13 rpm. It was also found that the highest amount of BC was obtained when the space between two adjacent discs was adjusted to 1 cm and the disk number was 16. An aquarium pump was used to investigate the impact of aeration on RBC made of 12 integrated polyethylene discs and operated at optimal rotation speed of 13 rpm. Disk spacing distance was adjusted to 1.5 cm to consider the possible increasing of the thickness of BC film by aeration. Wet weight and dry weight of BC resulted from aerated fermentation increased more than 64 and 47%, respectively as compared to non-aerated RBC. In comparison with static culture, wet weight and dry weight of BC produced in aerated RBC fermentation increased more than 90.7 and 71%, respectively. Nanoscale structure of produced bacterial cellulose was confirmed by SEM analysis.

The performance of a continuously operated laboratory-scale rotating biological contactor (RBC) was assessed for the removal of heavy metals viz. Cu(II), Cd(II) and Pb(II) from synthetic wastewater using artificial neural networks (ANNs). The RBC was inoculated with Sulfate Reducing Bacteria consortium (predominantly Desulfovibrio species), and the performance was evaluated at different hydraulic retention times (HRTs) and inlet heavy metal concentrations. A feed-forward back-propagation neural network model was developed using 90 data sets obtained over a period of three months, to predict the removal of heavy metal (HMRE) and COD (CODRE). The predictive capability of the model was evaluated in terms of the coefficient of determination (R) and mean absolute percentage error between the model fitted and actual experimental data, whereas sensitivity analysis was performed on the input parameters by determining the absolute average sensitivity (AAS) values. The higher AAS value of the HRT compared with that of inlet heavy metal concentration suggested that the change of HRT has a significant influence on HMRE and CODRE. Overall, the results obtained from this study demonstrated that ANNs can efficiently predict RBC behaviour with regard to heavy metal and COD removal characteristics under the prevailing operational conditions.

The accelerating pace of global population growth, urbanization, and industrialization is exerting considerable pressure on freshwater resources. In developing countries, where infrastructure constraints often hinder the adoption of advanced treatment technologies, cost-effective and efficient wastewater solutions are essential. Algal–bacterial bioremediation represents a promising, eco-friendly method for removing organic pollutants through biological processes. This study evaluates a hybrid treatment system composed of three ponds: a covered anaerobic pond for organic matter digestion, a microalgal pond equipped with rotating biological contactors (RBCs) that facilitate interactions between heterotrophic bacteria and diatoms, and a final settling pond. Granular activated carbon embedded within the RBC enhances biofilm formation by attracting heterotrophic bacteria, thereby increasing treatment efficiency. Under optimal conditions—10 g of activated carbon and 1.7 d hydraulic retention time—the system achieved removal efficiencies of 95.8% for total suspended solids (TSS), 96.3% for turbidity, 85% for biological oxygen demand (BOD), and 99.9% for Escherichia coli. Bacteriological analysis showed complete removal of fecal coliform and total coliform. The characteristics of the outflow treated wastewater are 3 mg/L, 0.9 NTU, and 3.2 mg/L for TSS, turbidity, and BOD, respectively, while E. coli detection is under detection limit. The treated effluent complies with Category A for the reuse of treated wastewater in the Egyptian code for the reuse of treated municipal wastewater for agricultural purposes, offering a scalable and sustainable solution for wastewater management in resource-constrained regions.

Conventional wastewater treatment plants (WWTPs) are not able to remove completely some emerging contaminants, such as residual pharmaceutical compounds (PCs) with potential ecotoxicity to water bodies. An advanced bio-oxidation process (ABOP) using white-rot fungi (WRF) has been proposed as alternative biological treatment for degradation of non-biodegradable compounds. A synthetic and real wastewater spiked with 12 PCs at 50 μg L −1 was treated by means of ABOP based on WRF in a rotating biological contactor (RBC) at 1 day of hydraulic retention time (HRT). The ABOP achieved a remarkable biological performance in terms of TOC removal and reduction of N-NH 4 + and P-PO 4 3− nutrients. Likewise, 5 of the 12 PCs were eliminated with removal efficiencies ranging from 80 to 95%, whereas 6 of 12 PCs were eliminated with removal values ranging from 50 to 70%. The anaerobic digestion of the fungal sludge generated upon the treatment was also evaluated, obtaining a methane yield of 250 mL CH 4 g VS −1 . These results evidenced that the proposed ABOP is a promising alternative for the sustainable wastewater treatment of urban effluents, combining advanced oxidation with biological operation for the removal of emerging PCs and energy recovery.

A high-rate biological contactor process (HRBC) can be used as primary treatment instead of a clarifier to remove particulate, colloidal and soluble fractions of organic matter via biosorption plus flotation and divert it to anaerobic digestion for methane production, simultaneously reducing secondary aeration energy demand. Pilot and bench tests were conducted at a range of contact times (15–60 min) and contactor dissolved oxygen (DO) (0.2–2.0 mg/L) using waste activated sludge (WAS) from a trickling filter/solids contact (TF/SC) process in the HRBC. Biosorption performance was lowest when contact times were <30 min and unstable at DO < 0.5 mg/L. The overall average of 20% sCOD capture was similar to previous findings by others using WAS from conventional AS. The biomethane potential (BMP) of the HRBC float material can be as high as that of primary sludge (340–400 mL CH4/g VS), which is much greater than WAS. Operating the HRBC with a long contact time (>30 min) or with high DO (>1 mg/L) increases the amount of biosorption but reduces the BMP of the float. It was also found that biosorption only effectively occurs when a WAS is paired with the wastewater from the same facility.

The presence of micropollutants that include endocrine-disrupting compounds (EDC) in aquatic environments is currently one of the most relevant aspects of water quality due to their adverse effects on aquatic organisms and human health. From the several categories of EDC, 17β-estradiol (E2) is a natural hormone, which is prevalent in vertebrates, associated with the female reproductive system and maintenance of the sexual characters. 17α-Ethinylestradiol (EE2) is a synthetic hormone produced from the natural hormone E2 and is an essential component of oral contraceptives. These compounds are susceptible to bioconcentration and have high potential to bioaccumulation. Wastewater treatment plants are the main point source of E2 and EE2 into aquatic environments, but conventional wastewater treatment systems are not specifically designed for steroid removal. To overcome this problem, biological tertiary treatment may be a solution for the removal of emergent pollutants such as E2 and EE2. The main purpose of the present study is to provide a solution based on the optimization of a rotating biological contactor system to remove estrogens, specifically E2 and EE2, and to quantify their removal efficiency on different matrices, namely real wastewater and different synthetic wastewaters. All assays presented viable removal efficiencies for compound E2 with values always above 50%; real wastewater yielded the highest removal efficiencies. EE2 removal had better removal efficiencies with synthetic wastewater as feed solution, with removals above 15%, whereas the removal efficiency with real wastewater was inexistent.

Low strength wastewaters (LSW) are those that have a chemical oxygen demand COD < 1000 mg/L. Nitrogen and phosphorus are the major nutrients present in LSW in addition to the organic carbon. The present study was undertaken to develop an optimal combined treatment system for removing nitrogen from LSW at high hydraulic loading rates as there are hardly any reports on the same. The biological removal of carbon in LSW has been studied in detail earlier using the anaerobic hybrid reactor (HR) and activated sludge process (ASP). The biological nitrogen removal was studied through the conventional route of nitrification process. The effect of different operational parameters was studied to optimize the nitrification in rotating biological contactor (RBC) and aerobic HR. RBC showed better nitrification rate over aerobic HR.