Nutrient sequestration and lipid production potential of Chlorella vulgaris under pharmaceutical wastewater treatment: experimental, optimization, and prediction modeling studies.

Abstract

The efficient management and treatment of pharmaceutical industry wastewater (PIWW) have become a serious environmental issue due to its high toxicity. To overcome this problem, the present study deals with the phycoremediation of PIWW using Chlorella vulgaris microalga isolated from the Ganga River at Haridwar, India. For this, response surface methodology (RSM) and artificial neural network (ANN) tools were used to identify the best reduction of total phosphorus (TP) and total Kjeldahl's nitrogen (TKN) based pollutants along with the lipid production efficiency of C. vulgaris. Three different concentrations of pharmaceutical wastewater (0, 50, and 100%), operating temperatures (20, 25, and 30 °C), and light intensity (2000, 3000, and 4000 lx) were used to design the phycoremediation experiments having 6:18 h of dark/light period and reactor functional volume of 15L. Findings revealed that C. vulgaris was good enough to remove maximum TP (90.35%), TKN (83.55%) along 20.88% of lipid yield at 25.62 °C temperature, 60.73% PIWW concentration, and 4000 lx of light intensity, respectively. Based on the model performance and validation results, ANN showed more accuracy as compared to the RSM tool. Therefore, the findings of this study showed that C. vulgaris is capable of treating PIWW efficiently along with significant production of lipid content which can further be used in various applications including biofuel production.