Water Stress Reduction Using Superstructure-Based Mathematical Model: Synthesise a Wastewater Treatment Plant Associated with Nutrient Recovery for Palm Oil Industry

Water stress is one of the major risks from climate change. Despite the extensive issue, improper treatment of wastewater further aggravates the issue of water stress. The agriculture sector is one of the major contributors towards water pollution. The nutrients such as nitrogen and phosphorus may flow into surrounding rivers and lakes and runoff from farming land may pollute groundwater, which affects food security, human health, aquatic ecosystems and water quality. Instead of disposal, the nutrients could be recovered from wastewater and turned into profits. Wastewater treatment is a vital process to treat wastewater produced in order to comply with stringent discharge limit. Nonetheless, designing a well-established WWTP is not easy. Previously WWT technologies are chosen from various wastewater treatment (WWT) technologies according to uncertain assumptions, knowledge or past experience of specialists. This method of choosing has the probability to cause significant loss of investment. Furthermore, recently, the practice in the industries has a paradigm change where sustainability of the process is becoming one of the focus. Thus, elements such as operating cost and carbon emission of each technology selected have to be considered when synthesising WWTP. Palm oil mill effluent (POME) contains substantial amount of valuable nutrients that can be recovered to increase the profit of WWTP. Thus, this paper aims to develop a decision-making tool using superstructure-based mathematical modelling for WWTP synthesis along with nutrient recovery technologies taking into consideration economic and environmental factors while comply with discharge limit, at the same time to reduce the risk of water stress. As multi-factors are considered, fuzzy multi-objectives optimisation (FMOO) is employed in the work by bringing together the objectives into a single parameter which is the degree of satisfaction, λ, to generate unbiased solution. A Malaysian oil palm industry case study is exemplified in this study to treat POME for palm oil industries using the developed approach. As a result, the optimal wastewater treatment process with optimum operating cost of RM 588/day, carbon emission of 118 kgCO2 eq/day, and profit of RM137/day gained from nutrient recovery is synthesised.