Suppr超能文献

微塑料纤维沉降速度的改进:一种新的形状相关阻力模型。

Improved Settling Velocity for Microplastic Fibers: A New Shape-Dependent Drag Model.

作者信息

Zhang Jiaqi, Choi Clarence Edward

机构信息

Department of Civil Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR.

出版信息

Environ Sci Technol. 2022 Jan 18;56(2):962-973. doi: 10.1021/acs.est.1c06188. Epub 2021 Dec 28.

Abstract

Microplastics are abundant in aquatic environments and are an emerging environmental concern. The prediction of their settling velocities is central to predictions of the residence time and concentration depth profiles of microplastics in aquatic environments. The main scientific challenge in improving the current understanding of the settling motions of microplastics is that existing drag models are deficient at reasonably predicting the settling velocities of various microplastics, especially microplastic fibers. This is because the shape factors used in the existing drag models cannot morphologically distinguish fibers from fragments and films. In this study, a new shape factor, specifically the Aschenbrenner shape factor, is proposed as a vehicle to explicitly distinguish among the morphologies of fibers, films, and fragments. With this new shape factor, a new drag model is developed and then systematically evaluated against the unique set of data provided by new experiments conducted in this study along with four other published data sets in the literature. The proposed model allows the prediction of the terminal settling velocity of microplastic fibers more accurately than existing drag models. Moreover, the new model has also shown its applicability to microplastic films and fragments. Notwithstanding, the new model appears deficient at reasonably predicting the terminal settling velocity of weathered microplastics in the field, which requires further investigations.

摘要

微塑料在水生环境中大量存在,是一个新出现的环境问题。预测它们的沉降速度是预测微塑料在水生环境中的停留时间和浓度深度分布的关键。当前在增进对微塑料沉降运动理解方面的主要科学挑战在于,现有的阻力模型在合理预测各种微塑料,尤其是微塑料纤维的沉降速度方面存在不足。这是因为现有阻力模型中使用的形状因子无法从形态上区分纤维与碎片及薄膜。在本研究中,提出了一种新的形状因子,即阿申布伦纳形状因子,作为一种能够明确区分纤维、薄膜和碎片形态的工具。利用这个新的形状因子,开发了一种新的阻力模型,然后根据本研究中进行的新实验以及文献中的其他四个已发表数据集所提供的独特数据集进行系统评估。所提出的模型比现有阻力模型更准确地预测微塑料纤维的终端沉降速度。此外,新模型也已显示出其对微塑料薄膜和碎片的适用性。尽管如此,新模型在合理预测现场风化微塑料的终端沉降速度方面似乎存在不足,这需要进一步研究。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验