Optimisation of Phytoremediation Process for Ammoniacal Nitrogen Reduction in Wastewater

Ting, Winnie Huong Tien (2019) Optimisation of Phytoremediation Process for Ammoniacal Nitrogen Reduction in Wastewater. Masters thesis, Universiti Malaysia Sarawak (UNIMAS).

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Abstract

Excessive nutrients deposition including ammoniacal nitrogen (AN) has led to eutrophication phenomenon, a serious environmental issue that endangers the aquatic ecosystem. The inefficiency and inadequacy of the current AN removal technologies have led to the high AN content in semiconductor industrial effluent. In order to comply with the standard discharge limit of 20 mg/L, a proper AN removal mean is necessary, in which water hyacinth-based phytoremediation technology is recommended as a cost-effective and environmental friendly solution. This research aims to investigate the feasibility of water hyacinth-based phytoremediation treatment system for AN removal. The research methodology consisted of AN tolerance limit study, semiconductor effluent characterisation, phytoremediation mechanism study, one-factor-at-a-time (OFAT) study and optimisation study. From tolerance limit study, water hyacinth showed its potential in treating wastewater with AN concentration ranging from 10 mg/L to 150 mg/L under sunlight exposure condition. Meanwhile, the mechanism study demonstrated that AN uptake by the plant was the significant mechanism for removing AN from wastewater using phytoremediation process, at which AN was absorbed by the plant roots followed by translocation and accumulation at different parts of the plant. OFAT study revealed that the growth condition of water hyacinth directly reflected on the AN removal efficiency, thus it was recommended to implement the phytoremediation system which was favourable to the plant’s growth, which was pH (5-9), initial AN concentration (10-50 mg/L), initial macrophytes density (10-30 g/L) and salinity (0-3 g NaCl/L). Through optimisation study, five empirical models were successfully developed by using Response Surface Methodology (RSM). Through numerical optimisation, the highest AN removal efficiency of 77.48% (initial AN concentration = 40 mg/L) was obtained at the following optimum conditions: pH of 8.51, retention time of 8.47 days, macrophyte density of 21.39 g/L and salinity of 0 g NaCl/L. The values predicted from the models agreed satisfactorily with the experimental values, which implied that RSM was reliable and practical for experimental design developed using optimisation of the phytoremediation process. The validation experiment using real semiconductor effluent further supported the high potential of the water hyacinth-based phytoremediation system to remove AN and other organic pollutants contents in this industrial effluent under optimal condition.

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