Detection of the presence of microplastics in textile industry process wastewater and evaluation of their removal using the circular economy model approach
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Abstract (EN)
In this study, firstly, the presence of microplastics discharged from the dye bath after the dyeing of the raw fabric woven from weft and warp threads produced from 100% recycled pet bottles (R-PET) was investigated by microscopic and elemental analysis methods. New, sustainable adsorbent material alternatives for the removal of microplastics in wastewater have been obtained from textile mill cellulose-based textile waste. Although the process conditions in adsorbent production are fixed, due to the low performance of the adsorbents obtained from the production of recycled cotton/viscose blend yarn waste in repeated experiments in methylene blue solution, the solution is prepared by adding Reduced Graphene Oxide (rGO) nanoparticles, which have a very high adsorption capacity, and lyocell-based adsorbent at different rates and using the solution under magnetic influence. Material (SFNK) doped with spinel ferrite was obtained in order to be easily separated from the environment. Elemental analyzes of the adsorbent material produced within the scope of the thesis study were carried out. Optimum adsorption conditions were determined by carrying out methylene blue dyestuff removal studies with the adsorbent obtained from 100% lyocell-based yarn waste, which provides the most reproducible and most efficient removal results in a laboratory environment. Microplastic removal in wastewater was tested under specified adsorption conditions. The desorption conditions of this adsorbate, which is successful in microplastic removal, in methylene blue solution were first investigated and its desorption performance in dye bath process wastewater was examined under these conditions.
Author
Gözde Abacı
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Gözde Abacı (Master Thesis). Detection of the presence of microplastics in textile industry process wastewater and evaluation of their removal using the circular economy model approach, 2024, Tekirdağ Namık Kemal University.
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