Date of Award
Doctor of Philosophy (PhD)
College of Science and Mathematics
Earth and Environmental Studies
Thesis Sponsor/Dissertation Chair/Project Chair
Robert W. Taylor
Stefanie A. Brachfeld
Eric A. Stern
This study focuses on the arsenic-affected rural communities in Bihar located within the mid-Gangetic Plain in India. A random stratified sampling method is applied to survey 340 households in three villages (Suarmarwa, Rampur Diara, and Bhawani Tola), through a structured questionnaire. A reliable arsenic field testing kit is used to analyze the drinking water sources in the field, followed by a confirmatory test of a subset of water samples through Atomic Absorption Spectrophotometry. The study has two major goals: 1) Develop sustainable arsenic-mitigation models; and 2) Create a “composite vulnerability index,” and present the information as a map for use in targeting of areas for intervention and policy-making.
Arsenic levels exceeding the World Health Organization and the Bureau of Indian Standards (max=300μg/L) were observed in all three villages. The hazard quotient and cancer risks for children in all three villages were high and very high, respectively. Arsenic treatment units and piped water supply systems were the most preferred sustainable arsenic-mitigation options in the surveyed villages, followed by deep tube wells, dug-wells, and rainwater harvesting systems. Arsenic awareness, willingness to pay for arsenic-free water, trust in agencies, trust in institution, and social capital were found to be the most significant factors for decision-making to prefer one arsenic-mitigation technology to others.
The surveyed respondents perceive health and economic risks more so than social discrimination risks with regard to arsenic-contaminated groundwater, and were more willing to adopt arsenic-mitigation technologies. The strongest predictors of health-risk perception were caste, education, agricultural-landholdings, housing status, and social capital. Predictors of economic-risk perception were caste, education, income, sanitation practices, people’s prioritization of socio-environmental problems, arsenic awareness, social capital, institutional trust, and social trust. Predictors of social discrimination risk were agricultural landholdings, people’s prioritization of social problems, arsenic awareness, institutional trust, and social capital.
Katihar in Bihar, with the least adaptive capacity and high vulnerability to arsenic contamination, should be prioritized in arsenic-mitigation policies. With a high level of adaptive capacity in Bhojpur district, the likelihood of success of arsenic-mitigation technology is the highest. A program utilizing expensive arsenicmitigation technologies will not work in the Vaishali, Samastipur, Khagaria, and Purnia districts.
Singh, Sushant Kumar, "Assessing and Mapping Vulnerability and Risk Perceptions to Groundwater Arsenic Contamination : Towards Developing Sustainable Arsenic Mitigation Models" (2015). Theses, Dissertations and Culminating Projects. 80.