CAREER: Marine Debris at Coastlines: predicting sources from drift, dispersion, and beaching via experiments and multiscale stochastic models

职业：海岸线的海洋碎片：通过实验和多尺度随机模型预测漂移、分散和搁浅的来源

• 批准号: 2338221
• 负责人: Nimish Pujara
• 金额: $ 56.39万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2028-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2338221&HistoricalAwards=false
• 关键词: CAREER; Marine; Debris; Coastlines; predicting

Floating marine debris in oceans and lakes across a range of sizes from microplastics to larger debris is a pressing global issue with inputs projected to increase in the coming years and decades. Often, the worst impacts of marine debris pollution are at coastlines, where economies and ecosystems are much more sensitive to pollution and where debris can accumulate to high concentrations. Current knowledge of marine debris motion near coastlines is insufficient to predict how debris drift, disperse, and become beached. This project seeks to fill this knowledge gap by investigating the fate and transport of marine debris at coastlines. This research will produce new and more accurate models for how particles of different sizes and complex shapes interact with and are transported by complex wavy and turbulent flows at coastlines. The project will also include significant educational activities, including an initiative to leverage expertise across institutions to improve graduate student training and increase participation of students from diverse backgrounds in engineering research in partnership with a local high school.The goal of this project is to construct a multiscale stochastic model of marine debris at coastlines that includes how debris particles drift, disperse, and become beached. While most efforts in marine debris research have concentrated on characterizing pollution in open waters and in beach sediment, this project will consider how the complexities of debris size, shape, and density combine with the complexity of flow conditions in the coastal environment to determine marine debris fate and transport. Experimental and theoretical approaches at multiple scales will produce the parameters required to populate the overall model. On the experimental side, this will include advanced flow and particle tracking methods in different water wave flumes and basins. On the theoretical side, this will include discovering appropriate scaling relationships and dimensionless descriptions of debris drift, dispersion, and beaching through mathematical modelling and experimental data analysis. Overall, the results are expected to inform solutions for coastal protection against debris pollution. The project is co-funded by the NSF ENG/CBET Fluid Dynamics and Environmental Engineering programs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

海洋和湖泊中漂浮的海洋垃圾大小不一，从微塑料到更大的垃圾，这是一个紧迫的全球问题，预计未来几年和几十年的投入将增加。海洋垃圾污染的最严重影响往往发生在海岸线，那里的经济和生态系统对污染更为敏感，而且垃圾可以在那里高度聚集。目前对海岸线附近海洋垃圾运动的了解不足以预测垃圾如何漂移、扩散和搁浅。该项目试图通过调查海洋废弃物在海岸线的命运和运输来填补这一知识空白。这项研究将为不同大小和复杂形状的颗粒如何与海岸线上复杂的波浪和湍流相互作用和传输提供新的、更准确的模型。该项目还将包括重要的教育活动，包括一项倡议，利用各机构的专业知识来改进研究生培训，并与当地一所高中合作，增加来自不同背景的学生对工程研究的参与。该项目的目标是建立一个多尺度的海岸线海洋垃圾随机模型，其中包括垃圾颗粒如何漂移、扩散和搁浅。虽然海洋垃圾研究的大部分努力集中在确定开放水域和海滩沉积物中的污染特征，但该项目将考虑垃圾大小、形状和密度的复杂性与沿海环境中流动条件的复杂性如何决定海洋垃圾的命运和运输。多个尺度上的实验和理论方法将产生填充整个模型所需的参数。在实验方面，这将包括在不同的水波水槽和盆地中使用先进的流动和颗粒跟踪方法。在理论方面，这将包括通过数学建模和实验数据分析，发现碎片漂移、扩散和搁浅的适当比例关系和无量纲描述。总体而言，预计这些结果将为防止碎片污染的沿海保护提供解决方案。该项目由NSF ENG/CBET流体动力学和环境工程项目共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。