Arsenic in shallow aquifer in the eastern region of Bangladesh: insights from principal component analysis of groundwater compositions

Abstract

Probable sources and mechanisms of arsenic (As) release in shallow aquifer in eastern Bangladesh are evaluated using statistical analysis of groundwater compositions. Dissolved As in 39 samples ranged from 8.05 to 341.5 microg/L with an average of 95.14 microg/L. Ninety seven percent of wells exceed the WHO limit (10 microg/L) for safe drinking water. Principal component analysis is applied to reduce 16 measured compositional variables to five significant components (principal components--PCs) that explain 86.63% of the geochemical variance. Two component loadings, namely PC 1 and PC 2 (45.31% and 23.05%) indicate the natural processes within the aquifers in which organic matter is a key reactant in the weathering reactions. Four groups of wells are defined by the PCA and each group of wells represents distinct physicochemical characteristics. Among them, group III groundwater shows higher As concentration together with high concentrations of Fe, Mn, dissolved organic carbon, PO4(3-) and HCO3(-) than groups I and II. Speciation calculations suggest that only wells of group III are saturated with respect to siderite, and all groups of samples are supersaturated with respect of rhodochrosite. The relationship of As with these parameters in the different groups of wells of the study area suggests that reductive dissolution of Fe-Mn oxyhydroxides with microbially mediated degradation of organic matter is considered to be the dominant processes to release As in groundwater.

Seasonal and Inter-Annual Variability of Groundwater and Their Responses to Climate Change and Human Activities in Arid and Desert Areas: A Case Study in Yaoba Oasis, Northwest China

“…In other words, the new variable (principal component) can reflect the original information and is not repeated. PCA can replace the inter-correlated variables by the independent uncorrelated principal components to eliminate the effect of multicollinearity; given these abilities, it is widely applied in the field of groundwater resources (i.e., groundwater level [43], quality [44], and geochemistry [45]). The detailed principle and calculation steps are given in previous study [43].…”

“…The positive and negative signs indicate the positive and negative effects of influencing factors on the groundwater level [44]. From Equation (4), human activities, such as unreasonable mass exploitation, rapid population growth, and gradual expansion of irrigated area, had a strong negative effect on the groundwater level in recent years, which caused a dramatic drop in groundwater level.…”

Assessment of groundwater quality of Lakshimpur district of Bangladesh using water quality indices, geostatistical methods, and multivariate analysis

“…It has been found that chemometric methods are the most reliable approaches for data mining of matrices from environmental quality assessment (Astel et al 2007(Astel et al , 2008. Among the available chemometric methods, multivariate statistical analysis has been widely used for source apportionment of metals in soil and water in different parts of the world (e.g., Singh et al 2005;Halim et al 2010;Bhuiyan et al 2010;Li et al 2013;Machiwal and Jha 2015).…”

Understanding abiotic ferrihydrite re-mineralization by ferrous ions

“…It is also well established that the iron (III)(hydr)oxide system is redox sensitive; one iron oxide transforming into another depending on various conditions such as pH, temperature, presence of ferrous ions, anions such as chloride, sulfate, and oxyanions such as arsenic (Liu et al 2005(Liu et al , 2008aPedersen et al 2005;Yee et al 2006;Mukiibi et al 2008;Das et al 2011aDas et al , 2011b. In natural and engineered environments, reductive dissolution of the ferric minerals is commonly cited as a primary mechanism causing arsenic mobilization (Pedersen et al 2006;Ghosh et al 2006;Jing et al 2008;Nguyen and Itoi 2009;Borch et al 2010;Halim et al 2010;Burnol and Charlet 2010;Maity et al 2011). However, the degree of iron mobilization often does not correlate well with the degree of arsenic release (Islam et al 2004;Horneman et al 2004;Burnol et al 2007;van Geen et al 2006;Kocar et al 2006;Ghosh et al 2006;Borch et al 2010;Reza et al 2010).…”