An Implementation of a Decision Support Tool to Assess Treatment of Emerging Contaminants in India

Emerging contaminants have been increasingly studied over the past decade to improve the understanding of their fate, occurrence and toxicological effects on the environment and human health. Originally wastewater treatment plants were not designed to remove these pollutants of emerging concern. However, research is now focusing on determining which existing treatment unit processes are suited to their removal. This research sets out to determine suitable treatment options for thirty nine emerging contaminants including various Pharmaceuticals and Personal Care products. The treatment options used in this study are taken from a developed decision support tool (WiSDOM) which formulates wastewater trains/packages for treatment of wastewater in India. The tool also evaluates the performance of each optimal solution in terms of removal of conventional pollutants (such as biochemical oxygen demand, chemical oxygen demand, total nitrogen, total phosphorous, faecal coliform etc.), using multi-objective genetic algorithms and multi-criteria decision analysis. An Excel Spreadsheet Program (ESP) was developed as an add-on to the tool, allowing the ESP to take an initial concentration of any of the thirty nine emerging contaminant and pass it through the treatment trains (generated/selected by the WiSDOM tool) to determine the removal efficiency. Three scenarios were developed to analyse the removal of emerging contaminants in India. The scenarios were designed to capture the influence of different socio-economic contexts and wastewater characteristics on the treatment technology selection. The tool generated results suggest that the use of constructed wetlands can remove a large proportion of emerging contaminants, resulting in low energy requirements and operational costs and wildlife habitats. However, the land requirement for this process is not always suited to urban areas in India. Advanced oxidation processes were also efficient at removing emerging contaminants. However, the energy requirements for this process were high. Emerging contaminants have different physical and chemical properties; therefore, future evaluations of each chemical should be monitored separately to generate suitable technologies suited to optimal removal.