Assessing the characteristics of groundwater quality of arsenic contaminated aquifers in the blackfoot disease endemic area

Kuang Liang Lu, Chen Wuing Liu, Sheng Wei Wang, Cheng Shin Jang, Kao Hung Lin, Vivian Hsiu Chuan Liao, Chung Min Liao, Fi John Chang

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24 Citations (Scopus)


Redox couples approach and multivariate statistical techniques, including factor analysis, cluster analysis and discriminant analysis, were applied to evaluate and to interpret the complex groundwater quality in the blackfoot disease endemic area, Taiwan. Most groundwater samples were characterized as Na-Ca-HCO3 with HCO3- as the dominant anion. Total arsenic (As) concentration, predominantly as As3+, ranged from <1.0 to 562.7μg/L. The patterns of measured reducing potential were consistent with those values calculated from As couple, revealing the in situ environment enhanced the accumulation of As concentration in the groundwater. Factor analysis proposed a four-factor model, comprising salination, reductive dissolution of Fe/Mn oxyhydroxides, As reduction and chemical potential factor, and explained 89.94% of total variance in groundwater. Furthermore, two factors, reductive dissolution of Fe/Mn oxyhydroxides and As reduction, suggested that the decoupled reductive processes accounted for high As concentration in this area. Cluster analysis was adopted to spatially categorize the sampled wells into three main clusters and characterized by the factor scores of the four-factor model. Two-parameter (pH and Eh) model derived from discriminant analysis can be used for preliminary assessment to determine whether the As concentration exceeds 10μg/L with simple field measurements in this area.

Original languageEnglish
Pages (from-to)1458-1466
Number of pages9
JournalJournal of Hazardous Materials
Issue number2-3
Publication statusPublished - 2011 Jan 30

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution
  • Health, Toxicology and Mutagenesis


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