Deakin University
Browse

File(s) under permanent embargo

The impact of textile wet colouration on the environment in 2011

journal contribution
posted on 2012-01-01, 00:00 authored by Christopher HurrenChristopher Hurren, Qing Li, Xungai Wang
Wet textile colouration has the highest environmental impact of all textile processing steps. It consumes water, chemicals and energy and produces liquid, heat and gas waste streams. Liquid effluent streams are often quite toxic to the environment. There are a number of different dyeing processes, normally fibre type specific, and each has a different impact on the environment. This research investigated the energy, chemical and water requirements for the exhaust colouration of cotton, wool, polyester and nylon. The research investigated the liquid waste biological oxygen demand, total organic carbon dissolved solids, suspended solids, pH and colour along with the energy required for drying after colouration. Polyester fibres had the lowest impact on the environment with low water and energy consumption in dyeing, good dye bath exhaustion, the lowest dissolved solids levels in waste water, relatively neutral pH effluent and low energy in drying. The wool and nylon had similar dyebath requirements and outputs however the nylon could be dyed at far lower liquor ratios and hence provided better energy and water use figures. Cotton performed badly in all of the measured parameters.

History

Journal

Advanced materials research

Volume

441

Pagination

540 - 543

Publisher

Trans Tech Publications

Location

Stafa-Zurich, Switzerland

ISSN

1022-6680

Language

eng

Notes

Presented at the 2011 International Conference on Eco-Dyeing, Finishing and Green Chemistry (EDFGC)

Publication classification

C1 Refereed article in a scholarly journal; C Journal article

Copyright notice

2012, Trans Tech Publications, Switzerland

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC