Chemical and physicochemical characterization of effluents from the tanning and textile industries in Bangladesh with multivariate statistical approach.

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ID: 109805
2019
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Abstract
Industrial effluents are one of the foremost concerns relating to the anthropogenic environmental pollution. The effluents from the tanning and textile industries in Dhaka, Bangladesh, were characterized chemically and physicochemically with multivariate statistical techniques. The concentrations of heavy metals viz., Pb, Cd, Cr, Mn, Fe, Ni, Cu, and Zn were determined by atomic absorption spectrometer while concentrations of anions viz., F, Cl, NO, NO, and SO were measured by ion chromatograph. The physicochemical parameters viz., temperature, pH, electrical conductivity (EC), salinity, turbidity, dissolved oxygen (DO), and biological oxygen demand (BOD) were measured by a multiparameter meter while total suspended solids (TSS) and total dissolved solids (TDS) were measured gravimetrically. This study showed that effluents from both industries demonstrated high levels of TSS, TDS, EC, and heavy metals. Tannery effluents have lower pH and DO, and higher BOD, Cl, SO, and Cr concentrations while textile dyeing effluents have higher pH, NO, and NO concentrations, compared to the standard limits promulgated by the Bangladesh government. Multivariate statistical techniques such as cluster analysis and principal component analysis along with the correlation matrices showed significant association among the measured parameters and identified pollution sources as well as effluent types in the study area which could be linked to the processes used in textile dying and tanning industries. This study will be useful for identifying pollutants emanating from the two industries and will guide future industrial aquatic studies where multiple industrial runoffs are concerned.
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ahsan2019chemicalenvironmental Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ahsan, Md Aminul;Satter, Farjana;Siddique, Md Abu Bakar;Akbor, Md Ahedul;Ahmed, Shamim;Shajahan, Md;Khan, Rahat;
Journal Environmental monitoring and assessment
Year 2019
DOI
10.1007/s10661-019-7654-2
URL
Keywords
environmental pollution physicochemical parameters heavy metals and anions industrial effluents multivariate statistical techniques

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