Bioremediation of Battery Scrap Waste Contaminated Soils Using Coco Grass (<i>Cyperus rotundus</i> L.): A Prediction Modeling Study for Cadmium and Lead Phytoextraction

Abstract

With the increasing demand for electronic devices that use batteries, e-waste is also becoming a major threat to the environment. Battery e-waste contains hazardous heavy metals that affect the health of the soil ecosystem. Thus, the present study evaluates the cadmium (Cd) and lead (Pb) phytoextraction potential of coco grass (Cyperus rotundus L.) grown in soils contaminated with battery scrap waste (BSW). Pot experiments were conducted to grow C. rotundus under different treatments (0%: control, T1: 1%, T2: 2%, T3: 3%, and T4: 4%) of BSW mixed with soil (w/w). The results showed that BSW mixing significantly (p C. rotundus and an increase in oxidative stress enzymes with an increase in BSW dose. The Pearson correlation studies also showed that soil HM concentration had a negative influence on the growth and biochemical parameters of C. rotundus. The bioaccumulation and translocation factor analysis showed that C. rotundus was a hyperaccumulator plant with a maximum accumulation of Cd and Pb (38.81 and 109.06 mg·kg−1) in root parts followed by the whole plant (277.43 and 76.10 mg·kg−1) and shoot (21.30 and 22.65 mg·kg−1) parts. Moreover, predictive models based on multiple linear regression (MLR) and artificial neural network (ANN) approaches were developed for Cd and Pb uptake by C. rotundus. Mathematical modeling results showed that soil properties were useful to construct quality MLR and ANN models with good determination coefficient (R2 > 0.98), model efficiency (ME > 0.99), and low root mean square error (RMSE C. rotundus on BSW-contaminated soils and reducing its environmental and health consequences.

Keywords

• hazardous waste
• heavy metals
• mathematical models
• phytoremediation
• soil pollution
• waste management