Recent developments in Artificial Neural Network (ANN), steady-state and transient modeling of gas-phase biofiltration process

Biofilter technology has played a significant role over several decades in providing clean air through removal of Volatile Organic Compounds (VOCs) and odor causing chemicals such as hydrogen sulfide from industrial polluted airstreams. Biofilters where biological oxidation process takes place are designed and installed in numerous industrial facilities including chemical manufacturing, food processing, solid waste recycling and wastewater treatment plants to control emissions of VOCs, and odors in order to comply with the air emission regulations and to provide clean breathable air. Biofilter mathematical models under steady-state and transient conditions are essential in order to design, scale-up and predict biofilter performance under different operating conditions. Similarly, Artificial Intelligence (AI) through the use of Artificial Neural Network (ANN) modeling of biofiltration process is also becoming important. This research provides a detailed discussion and review of the recent (i.e., the last two decades) and important studies related to ANN, steady-state and transient biofilter models.