Doctoral Dissertation Research: Inductive Construction of Multi-Dimensional Environmental Processes from Point Soil Data

博士论文研究：从点土壤数据归纳构建多维环境过程

• 批准号: 1819727
• 负责人: Thomas Bittner
• 金额: $ 1.3万
• 依托单位: SUNY at Buffalo
• 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: 2018-08-01 至 2020-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1819727&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Inductive; Construction

This doctoral dissertation research project will analyze the spatial and temporal distribution patterns of radioactive elements (radionuclides) released by a nuclear accident and will test new methods for assessing radioactive contamination levels in soils. This project will address the technical challenges that researchers and decision makers face when designing and conducting field measurement to determine soil contamination levels, and it will improve existing analytical methods currently used for environmental contamination incidents. Project findings will enhance mitigation strategies to reduce the impact of contaminants on human and environmental health. Monitoring radioactivity levels in soils is particularly important because elevated radioactivity can affect human health through external exposure and through ingestion of agricultural products or livestock products. By assessing the radioactivity levels in soils in the context of background topography and physical processes, this project will enhance the understanding of radionuclide behavior in landscapes. Such enhanced understanding will help policy makers make informed decisions about remediation and safety measures in the event of a contamination incident. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.Delineating distribution patterns of contaminants from a limited number of soil samples poses challenges, especially in mountainous terrain with mixed land-use types such as is the case in Fukushima Prefecture in Japan, where forests, farm fields, and residential areas were contaminated by the radioactive fallout following the Fukushima Daiichi Nuclear Power Plant accident precipitated by the Tohoku earthquake and tsunami in March 2011. The doctoral student will focus her attention on radiocesium, which becomes attached to clay soil particles (colloids) and becomes immobile. These colloids can gradually move downward in soils or are redistributed through surface runoff, erosion, and deposition. These characteristics raise two principal questions: (1) Do the soil samples collected at certain points reflect the influence of topography and physical processes? (2) Does the collected data represent an accurate picture of the contaminant distribution patterns and their changes? In the past, analysis of the spatial distribution of contaminants used correlation and clustering techniques or other analytic methods like semivariograms and kriging. Because the use those types of approaches were not satisfactory for sites like those in Fukushima, the doctoral student will use stepwise multi-spatial scale analysis that considers horizontal, diagonal, vertical, and temporal soil distributions. The multi-spatial scale analysis then will be combined with terrain structure analysis. The structure of terrain includessoil collection points, hillslopes, flow paths, and watershed patterns. By combining this terrain analysis with numerical or distance-based analysis at different scales, this project will employ a more sophisticated spatial analysis approach for mountainous landscapes. Although this project will focus on methods developed for the Fukushima area, this approach will have utility at other sites, including locales in the U.S., where background factors might affect radioactivity levels resulting from accidental dispersing of radioactive materials at various spatial scales.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.

该博士论文研究项目将分析核事故释放的放射性元素（放射性核素）的时空分布模式，并将测试评估土壤放射性污染水平的新方法。 该项目将解决研究人员和决策者在设计和进行现场测量以确定土壤污染水平时面临的技术挑战，并将改进目前用于环境污染事件的现有分析方法。 项目研究结果将加强缓解策略，以减少污染物对人类和环境健康的影响。监测土壤中的放射性水平尤为重要，因为放射性水平升高会通过外部暴露以及摄入农产品或畜产品影响人类健康。 通过评估背景地形和物理过程背景下土壤中的放射性水平，该项目将增强对景观中放射性核素行为的理解。 这种加深的了解将有助于政策制定者在发生污染事件时就补救和安全措施做出明智的决定。 作为博士论文研究改进奖，该奖项还将为有前途的学生建立强大的独立研究生涯提供支持。从有限数量的土壤样本中描绘污染物的分布模式提出了挑战，特别是在混合土地利用类型的山区，例如日本福岛县的情况，那里的森林、农田和住宅区受到了放射性沉降物的污染。 2011 年 3 月东北地震和海啸引发的福岛第一核电站事故。博士生将把注意力集中在放射性铯上，放射性铯会附着在粘土颗粒（胶体）上并变得不可移动。 这些胶体可以在土壤中逐渐向下移动，或者通过地表径流、侵蚀和沉积重新分布。 这些特征提出了两个主要问题：（1）在某些点采集的土壤样品是否反映了地形和物理过程的影响？ (2) 收集到的数据是否准确地反映了污染物的分布模式及其变化？ 过去，污染物空间分布的分析使用相关和聚类技术或其他分析方法，如半变异函数和克里金法。 由于这些类型的方法对于福岛等地点的使用并不令人满意，因此博士生将使用逐步多空间尺度分析，考虑水平、对角线、垂直和时间土壤分布。 多空间尺度分析将与地形结构分析相结合。 地形结构包括土壤收集点、山坡、水流路径和流域格局。 通过将地形分析与不同尺度的数值或基于距离的分析相结合，该项目将为山地景观采用更复杂的空间分析方法。 虽然该项目将重点关注为福岛地区开发的方法，但这种方法也适用于其他地点，包括美国的地区，这些地区的背景因素可能会影响由于放射性材料在不同空间尺度上的意外扩散而产生的放射性水平。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

项目成果

Assessment of ambient dose equivalent rate distribution patterns in a forested-rugged terrain using field-measured and modeled dose equivalent rates

使用现场测量和建模的剂量当量率评估森林崎岖地形中的环境剂量当量率分布模式

• DOI: 10.1016/j.radmeas.2023.106978
• 发表时间: 2023
• 期刊: Radiation Measurements
• 影响因子: 2
• 作者: Yasumiishi, Misa;Masoudi, Pedram;Nishimura, Taku;Ochi, Kotaro;Ye, Xiang;Aldstadt, Jared;Komissarov, Mikhail
• 通讯作者: Komissarov, Mikhail

Assessing the effect of topography on Cs-137 concentrations within forested soils due to the Fukushima Daiichi Nuclear Power Plant accident, Japan

评估日本福岛第一核电站事故造成的地形对森林土壤中 Cs-137 浓度的影响

• DOI: 10.5194/esurf-9-861-2021
• 发表时间: 2021
• 期刊: Earth Surface Dynamics
• 影响因子: 3.4
• 作者: Misa Yasumiishi;Taku Nishimura;Jared Aldstadt;Sean J. Bennett;and Thomas Bittne
• 通讯作者: and Thomas Bittne