Open AccessChemometric characterization of textile waste waters from different processes
Author(s) -
Tina Jerič,
Darinka Brodnjak Vončina,
Alenka Majcen Le Maréchal,
Darja Kavšek
Publication year - 2021
Publication title -
nova biotechnologica et chimica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.212
H-Index - 9
eISSN - 1339-004X
pISSN - 1338-6905
DOI - 10.36547/nbc.1272
Subject(s) - chemical oxygen demand , total suspended solids , total dissolved solids , turbidity , suspended solids , effluent , water quality , pulp and paper industry , biochemical oxygen demand , textile , chemistry , ammoniacal nitrogen , pollution , wastewater , environmental science , environmental engineering , materials science , engineering , ecology , oceanography , composite material , biology , geology
The aim of this work is focused on water quality classification of the textile waste water streams and evaluation of pollution. Data from the chemical characterization of the effluents were elaborated to identify a useful separation in potentially treatment for reuse. This was done with the aim of realizing a full scale characterization of effluents. In the two textile companies analyzed, machineries are used to carry out different production processes such as sizing and desizing, weaving, scouring, bleaching, mercerizing, carbonizing, fulling, dying and finishing. Different process effluents from the same machinery were found to be very diverse in pollution level. 25 and 49 samples of textile waste waters from two different textile companies were analysed and physical chemical measurements were performed. The following physicochemical and chemical water quality parameters were controlled: absorbance measured at three different wavelengths, pH, conductivity, turbidity, total suspended solids, volatile suspended solids, chemical oxygen demand, metals content (Ba, Ca, Cu, Mn, K, Sr, Fe, Al, Na) and total nitrogen content. For
handling the results, basic statistical methods for the determination of mean and median values, standard deviations, minimal and maximal values of measured parameters and their mutual correlation coefficients, were performed. Different chemometric methods, namely, principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA) were used to find hidden information about textile waste water quality.