RESUMO
This study was conducted to assess the phytoremediation potential of Pistia stratiotes for post-treatment of Ni(II) and Cr(III)-containing industrial wastewater effluents in mono (synthetic wastewater) and bimetallic systems (real wastewater). Differences were seen in metal uptake, growth performance, and metal accumulation of the plants. In the monometallic system, the highest removal efficiency was calculated as 77.50% for Cr(III) and 70.79% for Ni(II) at 5 mg L-1 concentration. At 1.25 mg L-1 concentration, the bioconcentration factor of P. stratiotes was calculated as 734.2 for Ni(II) and 799.0 for Cr(III). To assess the effects of metal stress on plants, photosynthetic pigments and percent growth rates were also investigated. The percent growth rate increased from 38.22 to 81.74% for Ni and decreased from 87.53 to 43.18% for Cr(III) when the metal concentrations increased from 1.25 to 5 mg L-1. Toxicity symptoms were less severe in plants exposed to low Ni concentrations. The greatest reduction in chlorophyll was observed at 5 mg L-1 Ni concentration. P. stratiotes showed better performance in the monometallic system. It was concluded based on present findings that P. stratiotes could potentially be used for the post-treatment of wastewaters containing Ni and Cr.Novelty Statement Previous phytoremediation studies were mostly conducted only in either mono- or multi-metallic systems. In this study, mono- and bimetallic systems were assessed together and the feasibility of research findings on a large scale was investigated in detail. Present findings may also aid in the development of phyto-remedial strategies and the identification of Ni and Cr toxicity in macrophytes. Pistia stratiotes are already known for its incredible potential in removing metals and other contaminants from wastewater effluents. However, most studies only present data regarding the plant performance in laboratory studies (synthetic wastewater), while this study provides some important additional information on natural effluent conditions, which transform the presented data more interesting from a practical point of view.