Pathogens removal from wastewater using sustainable treatment wetlands

This study aimed on assessing the performance of Waste Stabilization Ponds (WSPs) and Constructed Wetlands (CW) in removing pathogens from wastewater in Tanzania. It investigated factors that influence pathogens removal, which enabled developing mathematical model for better understanding of pathogens removal mechanism in Horizontal Sub-Surface Flow (HSSF) CW and finally improving the design of CW to enhance the removal process. The performance of WSPs and CW and mechanisms of pathogens removal from wastewater were assessed through experimental analysis. In which samples of wastewater were assessed through experimental analysis. in which samples of wastewater were collected from eight sites. Each site at least four times and were examined for pathogens presence. Assessed WSP and CW systems were found to have mean faecal coliform removal efficiencies of 2.58 〖log〗(10,) 2.74 〖log〗(10,) 2.13 〖log〗(10,) 2.07 〖log〗(10,) 2.08 〖log〗(10,)3.80 〖log〗(10,)3.80 〖log〗(10,) 1.99 〖log〗(10,) 0.98 〖log〗(10,) for Morogoro WSPs, Vingunguti WSPs, St. Antony CW, Ruaha CW, UDSM WSP, Mwanza WSPs, IRUWASA WSPs and IRUWASA CW, respectively. In case of parasites removal these treatment systems were found to have removal efficiencies of 99.46%, 89.61%, 100%, 99.88% 55%, 99.09, 99.17% and 100%, respectively. All treatment systems did not meet the effluent quality recommended by WHO based on faecal coliform (<1x〖10〗^3 cfu/100 mls). In case of parasites all effluents from CW met the recommended limit by WHO by having <1 egg and cysts/L, while all WSPs except the Vingunguti WSPs performrd better in removing faecal coliformed better in removing parasites achieving up to 100% removal. The pilot scale demonstrated that CW cell with 12 mm substrates performed better in removing faecal coliform (up to 2.74 〖log〗(10,)) compared to that with 20 mm at the same hydraulic retention time (HRT). Also higher removal efficiencies were observed at higher HRT (> 7 days). Developed mathematical model of CW showed better predictions on the system performance when related to experimental data. There was no significance difference between predicted and experimental values (p = 0.80). hence it was recommended to incorporate this model in the design of HSSF CW.