涤纶织物生产中改进的灰水足迹计算与评价方法

IF 0.6 4区 工程技术 Q4 MATERIALS SCIENCE, TEXTILES
Ke Wang, Xiaopeng Wang, Xiang Feng, Laili Wang
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引用次数: 1

摘要

灰色水足迹已被广泛用作量化纺织品对水环境影响的指标。传统上,灰色水足迹值是由典型水污染物的最大灰色水足迹确定的。废水中共存的其他关键化合物的性能被忽略。为了弥补灰色水足迹核算和评估的不足,本研究提出了一种改进的灰色水足迹计算和评估框架。考虑了污染物在河流中的扩散和衰减过程,对排放废水中各种污染物造成的影响进行了综合核算和评价。以涤纶织物生产为例说明了改进灰色水足迹计算与评价方法的应用。结果表明,化学需氧量对水体富营养化的影响最为严重,锑对水体生态毒性的影响最严重。改进灰色水足迹综合评价表明,碱剥离工艺对涤纶织物生产过程中的水环境影响最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Gray Water Footprint Calculation and Assessment Method for Polyester Fabric Production
Gray water footprint has been widely used as an indicator to quantify the water environmental impact of textile products. Traditionally, gray water footprint values are determined by the largest gray water footprint value of the typical water pollutant. The performances of other critical compounds that coexist in wastewater are disregarded. To mitigate these shortcomings associated with gray water footprint accounting and assessment, an improved gray water footprint calculation and assessment framework is proposed in this study. The diffusion and attenuation process of pollutants in rivers was considered for the comprehensive accounting and evaluation of the impacts caused by various pollutants in discharged wastewater. Polyester fabric production was used to illustrate the application of the improved gray water footprint calculation and assessment method. The results revealed that chemical oxygen demand caused the most severe water eutrophication impact and antimony caused the most severe water ecotoxicity impact. The comprehensive evaluation of improved gray water footprint indicated that alkali peeling process caused the largest water environmental impact during polyester fabric production.
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来源期刊
AATCC Journal of Research
AATCC Journal of Research MATERIALS SCIENCE, TEXTILES-
CiteScore
1.30
自引率
0.00%
发文量
34
期刊介绍: AATCC Journal of Research. This textile research journal has a broad scope: from advanced materials, fibers, and textile and polymer chemistry, to color science, apparel design, and sustainability. Now indexed by Science Citation Index Extended (SCIE) and discoverable in the Clarivate Analytics Web of Science Core Collection! The Journal’s impact factor is available in Journal Citation Reports.
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