Recent Trends of Arsenic Contamination in Groundwater of Ballia District, Uttar Pradesh, India

Abstract

Arsenic in the ground water is a worldwide problem as about 150 million people are at risk and more than 70 countries are suffering from this havoc. Arsenic is a carcinogen and responsible of various types of cancers. India is also having this problem in some parts including Ballia District, UP. The overall objective of this study is to study the mitigation of arsenic by using chemical data and GIS application.It is a GIS-based approach to monitor the changes in arsenic concentrations in different seasons in one year period. 100 samples were collected from deep, medium and shallow aquifer twice in pre-monsoon (April, 2010) and post-monsoon seasons (December, 2010). The samples were analyzed by atomic absorption spectrometer and correlated with geological features. A global positioning system (GPS) was used for locating the Sampling points, and a geographic information system was used for mapping and  interpolation of point data to assess the spatial variation of arsenic.With the help of GIS the correlation between arsenic contamination with geological features and seasonal variation were analyzed. The arsenic concentrations in shallow, medium and deep aquifers were 14-820, 30-450 and 6-300 ppb in pre-monsoon. But in post-monsoon these values were 13-950, 10-600 and 2-500 ppb, respectively. The seasonal variations were analyzed indicating high arsenic concentrations in post-monsoon season. These results indicated that arsenic mitigation is from shallow to medium and deep aquifers. Besides, many people were found to show arsenical lesions in the affected area.The concentration of arsenic is found in all blocks of the study area. There was evidence of seasonal variation in concentrations of arsenic between pre and post-monsoon seasons. The concentrations of arsenic were higher in post-monsoon than pre-monsoon due to insufficient rainfall during study year. 

Keywords

• GIS
• Arsenic contamination
• Aquifer
• Seasonal variations
• Water pollution;