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.

本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）的空间和时间分布模式，并将测试评估土壤中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实地测量以确定土壤污染程度时面临的技术挑战，并将改进目前用于环境污染事件的现有分析方法。 项目结果将加强缓解战略，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特别重要，因为放射性水平升高会通过外部照射和摄入农产品或畜产品影响人类健康。 该项目通过在背景地形和物理过程的背景下评估土壤中的放射性水平，将增进对放射性核素在景观中的行为的了解。 这种加深的了解将有助于决策者在发生污染事件时就补救和安全措施作出知情决定。 作为博士论文研究改进奖，该奖项还将为有前途的学生提供支持，使其能够建立强大的独立研究事业。从有限数量的土壤样本中描绘污染物的分布模式是一项挑战，特别是在土地利用类型混合的山区地形中，例如日本福岛县，那里的森林，农田，2011年3月东北地震和海啸引发的福岛第一核电站事故后，核电站和居民区受到放射性沉降物的污染。 博士生将把她的注意力集中在放射性铯上，放射性铯附着在粘土颗粒（胶体）上，变得不动。 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）在某些地点采集的土壤样品是否反映了地形和物理过程的影响？ (2)所收集的数据是否准确反映了污染物分布模式及其变化？ 在过去，污染物的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。 由于使用这些类型的方法是不令人满意的网站，如在福岛，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。 然后将多空间尺度分析与地形结构分析相结合。 地形的结构包括土壤收集点、山坡、水流路径和流域模式。 通过将这种地形分析与不同尺度的数值分析或基于距离的分析相结合，该项目将对山区景观采用更复杂的空间分析方法。 虽然该项目将侧重于为福岛地区开发的方法，但这种方法将在其他地点发挥作用，包括美国的地点，该奖项反映了NSF的法定使命，并通过使用基金会的知识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