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.

The non-linear complex relationships among the process variables in wastewater and waste gas treatment systems possess a significant challenge for real-time systems modelling. Data driven artificial intelligence (AI) tools are increasingly being adopted to predict the process performance, cost-effective process monitoring, and the control of different waste treatment systems, including those involving resource recovery. This review presents an in-depth analysis of the applications of emerging AI tools in physico-chemical and biological processes for the treatment of air pollutants, water and wastewater, and resource recovery processes. Additionally, the successful implementation of AI-controlled wastewater and waste gas treatment systems, along with real-time monitoring at the industrial scale are discussed.