Assessing the Groundwater Concentrations and Geographical Distribution of Arsenic in Nepal

Abstract:

Arsenic ₃₃As, one of the major groundwater contaminants, occurs in both natural and anthropogenic forms. Arsenic inhibits cellular respiration and the production of ATP in human body. Prolonged intake of non-lethal quantities of arsenic can cause cancer and diseases in vital organs such as the heart, liver, skin, and kidney. Each year, millions of people in the rural areas of Bangladesh, India, and other developing countries in South Asia are exposed to arsenic-poisoned groundwater. According to the World Health Organization, arsenic levels in drinking water should not exceed 10 parts per billion; however, the levels of arsenic found in groundwater in the heavily contaminated regions are often more than ten times of the recommended limit. Nepal is one of these regions. In most of the rural areas in Nepal, there is no infrastructure to produce clean filtered water, and wells thus became the major source. However, most of these wells were dug without testing for groundwater safety, because the test commands resources that the rural communities do not have access to. This is also limited data published on Nepal’s groundwater contaminant levels. The scarcity of information prohibits the international community from recognizing the severity of arsenic poisoning in Nepal and coming up with the most efficient measures to help. With this project, we will present a method to determine groundwater safety by analyzing geologic data and using remote sensing. The original source of arsenic is the arsenic-bearing minerals in the sediments. Some geological formations have higher arsenic levels than others due to their depositional environments. Therefore, by using existing geologic data from Nepal and countries with similar types of arsenic contamination, we hope to determine correlations between areas where there are reports of high concentrations of arsenic in groundwater to the environmental factors that may cause a particular concentration of arsenic. Furthermore, with deeper understanding of the correlations, we can predict whether an area is suffering from arsenic laden groundwater without actual field testing. We use R and ArcGIS to conduct the statistical and geographical analysis in this project.

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