Phytoremediation of palm oil mill secondary effluent using vetiver system

Malaysia is the second largest exporter of palm oil after Indonesia. It has contributed to environmental pollution due to the production of huge quantities of Palm Oil Mill Effluent (POME). Palm Oil Mill Secondary Effluent (POMSE) the product of secondary treatment of POME, is facing serious environmental issue due to not set compliance of discharge standard. The BOD 20 mg/L level is a difficult target from DOE and many mills have not been able to comply with it. To date chemical treatment methods are the only successful means in getting BOD to be less than 20 mg/L. The biological POME polishing system achieved BOD levels of < 20 mg/L, but it cannot be sustained due to biological failure and poor bacterial growth. A phytoremediation method (floating Vetiver system) was used to treat POMSE. A batch study using 40L treatment tanks was carried out under different conditions and Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were applied to optimize the treatment process. In this study POMSE concentration, Vetiver plant density and time have significant effects on the percentage removal of BOD, COD, TN, Color and TSS. An extraordinary decrease in organic matter as measured by BOD and COD (96% and 94%respectively) was recorded during the experimental duration of 4 weeks using a density of 30 Vetiver plants. The best and lowest final BOD of 2 mg/L was obtained when using 15 Vetiver plants after 13 days for low concentration POMSE (initial BOD= 50 mg/L). The next best result of BOD at 32 mg/L was obtained when using 30 Vetiver plants after 24 days for medium concentration POMSE (initial BOD= 175 mg/L). The study concluded that the Vetiver system is an effective method of polishing and treating POMSE to achieve stringent effluent standard. The comparison between RSM and ANN models by scale of Relative Standard Error (RSE) showed that ANN is more accurate in measuring treatment efficiency with an RSE of less than 0.45%, as opposed to 1.80% RSE with RSM