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Collaborative Research: Linking Dissolved Organic Matter Composition to Photochemical Reactivity

合作研究：将溶解的有机物成分与光化学反应性联系起来

基本信息

批准号：
1802388
负责人：
Christina Remucal
金额：
$ 23.48万
依托单位：
University of Wisconsin-Madison
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1802388&HistoricalAwards=false
关键词：
Collaborative Research Linking Dissolved Organic

项目摘要

Contaminants such as pesticides and pharmaceuticals are commonly found in lakes, rivers, and other surface waters. It is important to know how quickly these chemicals break down in the environment due to natural processes in order to assess their potential risks to humans and ecosystems. This research project studies the role of sunlight in the breakdown of pesticides and pharmaceuticals in a process known as photodegradation. Photodegradation is driven by the photochemical reactions of dissolved organic matter (DOM), which is a complex mixture of organic chemicals derived from plants and microorganisms that is found in all natural waters. The chemical composition of DOM is highly variable in different waters, and the different compositions influence how quickly pesticides and pharmaceuticals break down when exposed to sunlight. Therefore, this project will develop a framework to predict the relative photoreactivity of a wide variety of DOM samples collected from rivers, bogs, lakes, and wastewater treatment plants located in forested, agricultural, and urban watersheds. By developing predictive models based on DOM composition measurements, this research will lay the groundwork for predicting the degradation rates of chemicals in aquatic systems. If successful, this knowledge can be used to identify and isolate chemical contaminants in the Nation's natural waters, thereby protecting public health and the environment. This project aims to determine the link between the composition of dissolved organic matter (DOM) to its photochemical reactivity. While state-of-the-science techniques such as high-resolution mass spectrometry provide more information about DOM composition than ever before, it is still not possible to predict the reactivity of DOM based solely on its composition due to the heterogeneity of this complex mixture. This research collaboration between the University of Wisconsin-Madison and the University of St. Thomas will test the hypothesis that a combination of parameters derived from a variety of analytical techniques can be used to predict relative photochemical reactivity within a diverse set of DOM samples. The principal investigators hypothesize that a subset of the data produced by the different techniques contributes strongly to variance in DOM reactivity because each technique samples different populations of DOM. In order to test this hypothesis, river and lake samples will be collected from five watersheds (St. Louis River, Yahara, Northern Highlands, Minnesota River, and Mississippi River), as well as samples before and after disinfection at five wastewater treatment plants. Collectively, these sites represent the range of natural freshwaters that are impacted by polar contaminants, such as pesticides and pharmaceuticals. These samples will be characterized by UV-visible spectroscopy, antioxidant measurements, and both Fourier transform-ion cyclotron resonance (FT-ICR) and Orbitrap mass spectrometry. Photoreactivity will be assessed using probe studies to quantify the quantum yields and steady-state concentrations of reactive species and by experiments with five target pesticides and pharmaceuticals. Multivariate statistics, including multiple linear regressions, hierarchical cluster analysis, and principal component analysis, will be used to develop a novel framework to predict the relative photochemical reactivity of natural and effluent organic matter based on composition. Finally, this unique data set will be used to test whether Orbitrap mass spectrometry is able to provide sufficient information to replace the use of FT-ICR mass spectrometry in determining the molecular composition of DOM for reactivity studies.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.

诸如农药和药物等污染物通常存在于湖泊、河流和其他地表沃茨中。必须了解这些化学品在自然过程中在环境中分解的速度，以便评估其对人类和生态系统的潜在风险。该研究项目研究了阳光在农药和药物分解过程中的作用，称为光降解。光降解是由溶解有机物（DOM）的光化学反应驱动的，DOM是在所有天然沃茨中发现的来自植物和微生物的有机化学品的复杂混合物。DOM的化学成分在不同的沃茨中变化很大，不同的成分会影响农药和药物在阳光下分解的速度。因此，本项目将开发一个框架，以预测从森林，农业和城市流域的河流，沼泽，湖泊和污水处理厂收集的各种DOM样品的相对光反应性。通过建立基于DOM组成测量的预测模型，本研究将为预测水生系统中化学物质的降解速率奠定基础。如果成功的话，这些知识可以用来识别和隔离国家自然沃茨中的化学污染物，从而保护公众健康和环境。该项目旨在确定溶解有机物（DOM）的组成与其光化学反应性之间的联系。虽然高分辨率质谱等科学技术提供了比以往更多的DOM组成信息，但由于这种复杂混合物的异质性，仅根据其组成预测DOM的反应性仍然是不可能的。威斯康星大学麦迪逊分校和圣托马斯大学之间的这项研究合作将测试的假设，从各种分析技术得到的参数的组合，可用于预测相对的光化学反应在一个不同的DOM样品集。主要研究人员假设，由不同技术产生的数据的子集对DOM反应性的变化有很大的贡献，因为每种技术对DOM的不同群体进行采样。为了检验这一假设，将从五个流域（圣路易斯河、雅哈拉、北方高地、明尼苏达河和密西西比河）采集河流和湖泊样本，以及五个污水处理厂消毒前后的样本。总的来说，这些地点代表了受农药和药物等极性污染物影响的天然淡水的范围。这些样品将通过紫外可见光谱、抗氧化剂测量以及傅立叶变换离子回旋共振（FT-ICR）和轨道阱质谱进行表征。将使用探针研究来评估光反应性，以量化反应物种的量子产率和稳态浓度，并通过五种目标农药和药物的实验进行评估。多元统计，包括多元线性回归，层次聚类分析，和主成分分析，将被用来开发一个新的框架来预测天然和污水有机物的组成的基础上的相对光化学反应性。最后，这个独特的数据集将被用来测试是否轨道阱质谱能够提供足够的信息，以取代使用FT-ICR质谱在确定DOM的分子组成的反应性studies.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Seasonal and Spatial Variability of Dissolved Carbon Concentration and Composition in Lake Michigan Tributaries

DOI：
10.1029/2021jg006449
发表时间：
2021-10
期刊：
Journal of Geophysical Research: Biogeosciences
影响因子：
0
作者：
Stephanie M. Berg;R. Mooney;Megan B. McConville;P. McIntyre;Christina K. Remucal
通讯作者：
Stephanie M. Berg;R. Mooney;Megan B. McConville;P. McIntyre;Christina K. Remucal

Spatial and Temporal Variability of Dissolved Organic Matter Molecular Composition in a Stratified Eutrophic Lake