SGER: Deployment of Wireless Sensor Network for Analysis of Irrigation Effects on Subsurface Redox Conditions and Arsenic Mobilization in Bangladeshi Aquifer

SGER：部署无线传感器网络用于分析灌溉对孟加拉国含水层地下氧化还原条件和砷迁移的影响

• 批准号: 0605515
• 负责人: Jennifer Jay
• 金额: $ 2.87万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-15 至 2007-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0605515&HistoricalAwards=false
• 关键词: SGER; Deployment; Wireless; Sensor; Network

0605515 Jay This award supports travel and field expenses for the PI and colleagues, including two graduate students, to conduct research in Bangladesh as part of a multi-university and interdisciplinary team investigating the factors causing toxic concentrations of arsenic in shallow ground water of the Ganges Delta. High concentrations of arsenic in ground water constitute a major public health problem in Bangladesh, as tens of millions of people rely on contaminated ground water supplies for drinking water. Numerous cases of arsenicosis and arsenic-induced skin cancer have been reported, and this is regarded as one of the largest environmental poisonings in history. Specific goals of the project are to (i) deploy a wireless sensor network to test three hypotheses regarding mobilization of arsenic in shallow aquifers under rice paddies; (ii) field test a new software tool designed to aid in debugging run-time problems in sensor networks; and (iii) use the collected data to develop a reactive-transport model of subsurface redox conditions and how they are affected by irrigation. The proposed work is aimed at improving scientific understanding of the factors giving rise to arsenic mobilization in ground-water aquifers, a topic of considerable interest in environmental science and practical concern for management of this widespread problem. Previous studies have established that redox conditions play an important role in arsenic mobilization, but the nature of that role and how irrigation affects this remain unclear. The work also is aimed at advancing our experience with sensor networks in environmental systems and dealing with problems that arise in deploying sensitive sensors under harsh conditions. This experience will be useful relative to deployment of sensor networks for environmental observatories in the U.S. In addition, the study should improve general understanding of arsenic mobilization in aquifers that applies beyond Bangladesh; arsenic contamination of ground water also is a common problem in the U.S. This award is funded jointly by the Environmental Engineering Program and OISE.

0605515 杰伊 该奖项支持PI及其同事（包括两名研究生）在孟加拉国进行研究的差旅费和实地考察费用，作为多大学和跨学科团队的一部分，调查导致恒河三角洲浅层地下水中砷有毒浓度的因素。地下水中高浓度的砷是孟加拉国的一个主要公共卫生问题，因为数千万人依赖受污染的地下水供应饮用水。据报道，砷中毒和砷诱发皮肤癌的病例数不胜数，这被认为是历史上最大的环境中毒事件之一。该项目的具体目标是：（一）部署无线传感器网络，以测试三个假设的动员砷在浅含水层下稻田;（二）现场测试一个新的软件工具，旨在帮助调试运行时的问题传感器网络;和（三）使用收集到的数据，以开发一个反应性运输模型的地下氧化还原条件，以及它们是如何受到灌溉。拟议的工作旨在提高对引起地下水含水层中砷流动的因素的科学认识，这是一个在环境科学中引起相当大兴趣的专题，也是管理这一普遍问题的实际关切。以前的研究已经确定，氧化还原条件在砷动员中起着重要作用，但这种作用的性质以及灌溉如何影响这一点仍不清楚。这项工作还旨在推进我们在环境系统中的传感器网络方面的经验，并处理在恶劣条件下部署敏感传感器时出现的问题。这方面的经验将是有益的，相对于部署传感器网络的环境观测站在美国此外，这项研究应提高砷动员在含水层，适用于孟加拉国以外的一般理解;砷污染地下水也是一个共同的问题，在美国这个奖项是由环境工程计划和OISE共同资助。