Author
Listed:
- Sumaiya Rashid
(Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Sylhet-3100, Bangladesh.)
- Md. Altaf Hossain
(Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Sylhet-3100, Bangladesh.)
- Fahmida Ishaque
(Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Sylhet-3100, Bangladesh.)
- Md. Hafizur Rahman
(Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Sylhet-3100, Bangladesh.)
- Md. Joybor Rahman
(Department of Agricultural Construction and Environmental Engineering, Sylhet Agricultural University, Sylhet-3100, Bangladesh.)
Abstract
The potential of using German grass (Echinochloa polystachya) in FTWs (Floating Treatment Wetlands) to treat municipal wastewater was investigated in this study. This mesocosm-based study was conducted over a 7-day Hydraulic Retention Period (HRT) with a total of 28 experimental days following a Randomized Complete Block Design (RCBD) with four treatments and three replicates. To evaluate system efficiency, mean temperature, PH, total dissolved solids (TDS), and electrical conductivity (EC) were also measured along with nitrate and phosphate concentrations. On day 28, the nitrate removal rate obtained with Pickerel weed was 88.65 % while German grass showed 86.56 % of remediation. On the other hand, while Pickerelweed removed 9.5 % of phosphate, German grass removed 7.47 %. The study demonstrated that the use of German grass in FTWs can be highly effective in the removal of nitrate ions from wastewater, while the removal of phosphate ions was minimal.
Suggested Citation
Sumaiya Rashid & Md. Altaf Hossain & Fahmida Ishaque & Md. Hafizur Rahman & Md. Joybor Rahman, 2022.
"Remediation Of Nutrients From Municipal Wastewater Using German Grass-Aided Floating Treatment Wetland,"
Water Conservation & Management (WCM), Zibeline International Publishing, vol. 6(2), pages 107-114, November.
Handle:
RePEc:zib:zbnwcm:v:6:y:2022:i:2:p:107-114
DOI: 10.26480/wcm.02.2022.107.114
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