Decision Making Model for Municipal Wastewater Conventional Secondary Treatment with Bayesian Networks

Abstract

Technical, economic, regulatory, environmental, and social and political interests make the process of selecting an appropriate wastewater treatment technology complex. Although this problem has already been addressed from the dimensioning approach, our proposal in this research, a model of decision making for conventional secondary treatment of municipal wastewater through continuous-discrete, non-parametric Bayesian networks was developed. The most suitable network was structured in unit processes, independent of each other. Validation, with data in a mostly Mexican context, provided a positive predictive power of 83.5%, an excellent kappa (0.77 > 0.75), and the criterion line was surpassed with the location of the model in a receiver operating characteristic (ROC) graph, so the model can be implemented in this region. The final configuration of the Bayesian network allows the methodology to be easily extended to other types of treatments, wastewater, and to other regions.

Municipal Wastewater Treatment Technologies in Malaysia: A Short Review

“…Aerobic systems are suitable for the treatment of low-strength wastewaters, while anaerobic systems are suitable for high-strength wastewaters. Anaerobic treatment requires less energy and has the potential for bioenergy and nutrient recovery, but aerobic treatment achieves higher removal of soluble biodegradable organic matter, resulting in lower effluent suspended solids concentration and generally higher effluent quality [5,6]. The combination of these two approaches offers the potential for enhanced treatment efficiency and improved removal of pollutants.…”