Abstract

Environmental impacts of wastewater from textile and dyestuff industries are of growing concern due to limited freshwater availability and inadequate treatment facilities. Carbon nanotubes (CNTs) offer excellent adsorption potential because of their outstanding mechanical and chemical properties, however; their application in textile effluent treatment has not been widely studied. Moreover, laboratory-based studies are often costly and limited to a few variables, making it challenging to reveal the underlying relationships among several physicochemical parameters and CNT treatments. Multivariate statistical analysis (MVSA) offers an effective approach to overcome this challenge. To the best of our knowledge, no studies have integrated laboratory analysis of nanotube-based textile effluent treatment with an MVSA approach. This study aims to evaluate the physicochemical characterization of textile effluent, treat effluent with CNT, and explore the relationship between physicochemical parameters and CNT by integrating laboratory experiments with MVSA. For this purpose, single-walled CNT (SWCNT) and multi-walled CNT (MWCNT) were applied in batch mode adsorption experiments using various dosages and adsorption times. Scanning electron microscopy and Fourier transform infrared spectroscopy (FTIR), along with physicochemical analyses, were conducted to characterize the effluent and adsorption processes. The FTIR spectrum indicated that the absorption peaks of C=C, C=O, and the acidic f -OH group on CNTs enhance wettability and hydrophilic character, thereby increasing adsorption capacity. Experimental results demonstrated significant reductions in electrical conductivity (EC), total dissolved solids (TDS), turbidity, total organic carbon (TOC), and chemical oxygen demand (COD). CNT dosages of 1 to 5 g/100 mL and adsorption times of 2 to 5 h achieved removal efficiencies ranging from approximately 20% to 90% for SWCNT and MWCNT. MVSA indicated that MWCNT was more strongly associated with ionic and physical parameters (turbidity, TDS, EC, and pH), whereas SWCNT was more strongly related to organic load indicators, particularly COD and TOC. Overall, this study highlights the potential of CNT coupled with the MVSA technique as an effective and sustainable approach for textile wastewater treatment and offers valuable insights for researchers working in this field.

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