不同工艺纺织废水的化学计量学特征

Q4 Agricultural and Biological Sciences Nova Biotechnologica et Chimica Pub Date : 2021-11-22 DOI:10.36547/nbc.1272
T. Jerič, Darinka Brodnjak Vončina, Alenka Majcen Le Maréchal, Darja Kavšek
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引用次数: 0

摘要

本文主要研究纺织废水流的水质分类和污染评价。阐述了废水化学特性的数据,以确定在可能的回用处理中有用的分离。这样做的目的是实现污水的全面表征。在分析的两家纺织公司中,机械被用来进行不同的生产过程,如上浆和退浆、织造、练、漂、丝光、碳化、填充、染色和整理。研究发现,同一台机器的不同工艺废水的污染水平差异很大。对来自两家不同纺织公司的25个和49个纺织废水样本进行了分析,并进行了物理化学测量。控制了三种不同波长下的吸光度、pH值、电导率、浊度、总悬浮物、挥发性悬浮物、化学需氧量、金属含量(Ba、Ca、Cu、Mn、K、Sr、Fe、Al、Na)和总氮含量。为了处理结果,采用了确定测量参数的平均值和中位数、标准差、最小值和最大值及其相互相关系数的基本统计方法。采用主成分分析(PCA)、聚类分析(CA)和线性判别分析(LDA)等不同的化学计量学方法发现纺织废水水质的隐藏信息。
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Chemometric characterization of textile waste waters from different processes
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.
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来源期刊
Nova Biotechnologica et Chimica
Nova Biotechnologica et Chimica Agricultural and Biological Sciences-Food Science
CiteScore
0.60
自引率
0.00%
发文量
47
审稿时长
24 weeks
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