模拟明渠水流中的微塑料运输和底栖生物的摄取动力学

IF 12.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Mingming Jiao , Kai Wang , Chenwei Zhao , Yan Liu , Hongwei Fang
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引用次数: 0

摘要

了解水生环境中底栖生物无意摄入微塑料(MP)的动力学对于评估MP的生态影响至关重要。然而,人们对这一过程仍然知之甚少。为了解决这个问题,我们开发了一个高保真的双向耦合数值模型,该模型集成了大涡模拟和拉格朗日点粒子跟踪技术。研究了三个关键参数:底栖动物捕食类型(滤食动物、食草动物和穴居动物)、MP密度和底栖动物密度,其中底栖动物密度是主要因素。具体来说,底栖动物密度增加8倍会导致摄入的MPs增加5到22倍。底栖动物类型影响最终的摄食比例(定义为摄取与释放的MPs的比例),食草动物的摄食效率最高,其次是滤食性动物——在同等底栖动物密度下,两者的摄食率都是穴居动物的两倍左右。除高密度滤食动物外,MP密度对所有底栖动物种群和密度的摄食影响最小。在摄食过程中确定了两种不同的MP运输模式:(i)在滤食性动物中观察到的悬浮模式和(ii)在食草动物和穴居动物中普遍存在的滑动模式。劳斯数(P)有效地区分了这些模型,当P <;<;2.5时,悬架模式占主导地位,而当P >;>;2.5时,滑模模式占主导地位。劳斯数和湍流强度决定了每个底栖动物个体摄取MPs的数量,而所有底栖动物的累积捕食宽度决定了底栖动物密度和类型的影响。因此,这两个参数的乘积作为最终MP摄入比例的稳健预测器,其中在所有模拟中观察到强烈的线性关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Modeling microplastic transport in open channel flows and ingestion dynamics by benthos

Modeling microplastic transport in open channel flows and ingestion dynamics by benthos

Modeling microplastic transport in open channel flows and ingestion dynamics by benthos
Understanding the dynamics of unintentional microplastic (MP) ingestion by benthos in aquatic environments is crucial for assessing the ecological impacts of MPs. Yet, this process remains poorly understood. To address this, we developed a high-fidelity, two-way coupled numerical model that integrates large-eddy simulation and Lagrangian point-particle tracking techniques. Three key parameters are examined: benthos predation types (filter-feeders, grazers, and burrowers), MP density, and benthos density, with benthos density emerging as the dominant factor. Specifically, an eightfold increase in benthos density results in a 5- to 22-fold rise in ingested MPs. Benthos types influence the final ingestion proportion (defined as the ratio of ingested to released MPs), with grazers showing the highest ingestion efficiency, followed closely by filter feeders—both approximately doubling the ingestion rate observed in burrowers at equivalent benthos density. MP density has minimal influence on ingestion across all benthic groups and densities, except under high-density filter-feeder conditions. Two distinct MP transport models during ingestion are identified: (i) a suspension mode observed in filter-feeders and (ii) a sliding mode prevalent in grazers and burrowers. The Rouse number (P) effectively differentiates these models, with the suspension mode dominating when P < 2.5 and the sliding mode dominating when P > 2.5. The Rouse number and spanwise turbulence intensity govern the number of MPs ingested by each benthic individual, while the cumulative predation width of all benthos accounts for the impact of benthos density and types. Consequently, the product of these two parameters serves as a robust predictor for the final MP ingestion proportion, where a strong linear relationship is observed across all simulations.
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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