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优化微塑料分析以量化和识别洗衣废水中的微塑料纤维。

Optimising microplastics analysis for quantifying and identifying microplastic fibres in laundry wastewater.

作者信息

Tarte James V, Johir Md Abu Hasan, Tra Van-Tung, Cai Zhengqing, Wang Qilin, Nghiem Long D

机构信息

Centre for Technology in Water and Wastewater, University of Technology Sydney, NSW 2007, Australia.

Institute of Environmental Sciences, Nguyen Tat Thanh University, Ho Chi Minh City, Viet Nam.

出版信息

Sci Total Environ. 2024 Nov 20;952:175907. doi: 10.1016/j.scitotenv.2024.175907. Epub 2024 Aug 30.

Abstract

Current methods for measuring microplastic fibres (MPF) are cumbersome, time consuming and unscalable for routine high throughput analysis. This study reports a method for rapidly extracting, quantifying and analysing MPFs in laundry wastewater with several key improvements which vastly enhance overall efficiency and scalability of analysis. FT-IR surveying is employed as a preliminary step in analysis to quickly determine what polymers are present in a sample prior to fluorescence treatment. Using random quadrating, whole 25 mm filter membranes were surveyed in <30 min with high recovery rates. In industrial laundry wastewater samples, polyester was the most common MPF, however acrylic, nylon, cotton and rayon were all ubiquitous. The study also demonstrates that an excitation wavelength of 365 nm was optimal for fluorescing PET fibres like polyester which were stained with Nile Red, but not 495 nm, which is commonly used in microplastic analysis. Finally, a custom ImageJ macro was written to automatically enumerate and describe MPFs on filter membranes using just a single stitched fluorescence image. In just a few seconds, concentrations of up to 40,000 fibres/L were analysed in industrial laundry wastewater samples with a lower particle size limit of 20 μm. This study highlights the need for more optimised and scalable analysis workflows which maintain high levels of reliability and accuracy.

摘要

当前测量微塑料纤维(MPF)的方法繁琐、耗时,且无法用于常规高通量分析。本研究报告了一种用于快速提取、量化和分析洗衣废水中微塑料纤维的方法,该方法有几项关键改进,极大地提高了分析的整体效率和可扩展性。傅里叶变换红外光谱(FT-IR)测量被用作分析的初步步骤,以便在荧光处理之前快速确定样品中存在哪些聚合物。使用随机象限法,在不到30分钟的时间内对整个25毫米的滤膜进行了测量,回收率很高。在工业洗衣废水样本中,聚酯是最常见的微塑料纤维,不过丙烯酸、尼龙、棉和人造丝也都普遍存在。该研究还表明,365纳米的激发波长最适合使被尼罗红染色的聚酯等聚对苯二甲酸乙二酯(PET)纤维发出荧光,而不是微塑料分析中常用的495纳米。最后,编写了一个自定义的ImageJ宏程序,仅使用一张拼接的荧光图像就能自动计数和描述滤膜上的微塑料纤维。在短短几秒钟内,就对工业洗衣废水样本中浓度高达40000根/升、粒径下限为20微米的纤维进行了分析。本研究强调了需要更优化、可扩展的分析工作流程,以保持高水平的可靠性和准确性。

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