Abstract
Fish farm wastewater needs to be treated as it contains considerably high loading of suspended solids and dissolved nutrients from accumulation of by-products e.g. fish excretions and uneaten feed. In this study, macrophytes, namely Spirodela polyrhiza and Salvinia molesta were examined for their phytoremediation efficiency in treating fish farm wastewater in a raceway pond rig. It was carried out indoor for 14 days under controlled environment. Water samples was collected once every 2 days for analysis of NO3-- N, PO43-, NH3-N, COD, turbidity, MLVSS and pH. The results showed that there was decrement of phosphate in fish farm wastewater using either S. polyrhiza or S. molesta. Interestingly, S. polyrhiza was found to be more efficient in phosphate uptake as it removed 72% phosphate at day 4 and up to 95% in the end of the experiment whereas 72% phosphate removal was only achieved by S. molesta at day 10. Similar ammonia decrement was observed for both plants and most of the ammonia were not detected in the wastewater by day 10 for S. polyrhiza, while by day 8 for S. molesta. Nitrate showed increment for both plants which could be due to nitrification. Both plants achieved highest COD removal on day 12, whereby 68% for S. polyrhiza and 63% for S. molesta. They were able to reduce turbidity and total suspended solids (TSS) to very low level and significantly increase clarity of wastewater. S. polyrhiza reduced up to 96% of initial turbidity value and 86% of TSS. 82% reduction of initial turbidity and 79% TSS decrement were observed for S. molesta. pH fluctuations were minimum for both plants, with a range between 7.62 to 7.77. Both plants demonstrated biomass increment for fresh weight in which 84% for S. polyrhiza while 85% for S. molesta. This study proved that the macrophytes were able to treat fish farm wastewater by significantly removing phosphate, ammonia, turbidity and TSS. It aids in minimizing pollutants released to receiving waters and producing biomass which can be utilized for agriculture sector.
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