Assessment of groundwater quality, toxicity and health risk in an industrial area using multivariate statistical methods

• Published in: Environmental systems research Vol. 8; no. 1; pp. 1 - 17
• Main Authors: Krishna, A. Keshav, Mohan, K. Rama, Dasaram, B.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2019; Springer Nature B.V; SpringerOpen
• Subjects: Anions; Anthropogenic factors; Cadmium; Calcium; Calcium ions; Cations; Chromium; Cluster analysis; Contamination; Copper; Correlation analysis; Correlation coefficient; Correlation coefficients; Earth and Environmental Science; Environment; Factor analysis; Groundwater; Groundwater management; Health risk assessment; Health risks; Heavy metals; Human influences; Industrial areas; Industrial pollution; Industrial sites; Lead; Magnesium; Monitoring/Environmental Analysis; Multivariate analysis; Nickel; pH effects; Pollution sources; Principal components analysis; Quotients; Resource management; Risk analysis; Risk assessment; Seasons; Sodium; Statistical methods; Statistics; Summer; Total dissolved solids; Toxicity; Water pollution; Water quality; Water resources; Winter; Groundwater; Multivariate analysis; Risk assessment; Contamination; Water quality
• ISSN: 2193-2697; 2193-2697
• DOI: 10.1186/s40068-019-0154-0

Background This study investigates the common and anthropogenic activities that impact the science of groundwater in and around an industrial zone and exhibits the utilization of multivariate statistical methods for groundwater quality, toxicity and health risk associated with contaminated industrial sites for proficient administration of water assets. A total of 120 groundwater samples were collected during summer and winter season, and analyzed for their twenty physicochemical constituents including seven toxic heavy metals (pH, EC, total dissolved solids (TDS), F, K, Na, Ca, Mg, Cl, CO 3 , HCO 3 , NO 3 , SO 4 , As, Cd, Cr, Cu, Ni, Pb and Zn). Data obtained was treated using principal component analysis (PCA)/factor analysis (FA), hierarchical cluster analysis (HCA), Correlation coefficient and health risk analysis to find the common pollution source. Results The results for mean abundance during two seasons for cations and anions were 7 and 6.9 for pH; 1875 and 1527 for TDS; 3 and 3.3 (µs/cm) for EC; 655 and 569 for Ca 2 + ; 59 and 56 for Mg 2 + ; 340 and 211 for Na + ; 5 and 4 mg/L for K + ; 148 and 126 for CO 3 2− 301 and 228 for HCO 3 − ; 289 and 223 for Cl − 0.5 and 0.85 for F − ; 99 and 86 for SO 4 2− 28 and 23 mg/L for NO 3 − . While for heavy metals 18 and 4 for As; 2 and 0.4 for Cd; 29 and 5 for Cr; 17 and 4 for Cu; 25 and 6 for Ni; 82 and 3 for Pb; 953 and 989 µg/L for Zn, respectively. FA identified six dominant factors for each during summer and winter seasons that explained 70.43% and 71.06% of the variance in the dataset. Health risk assessment of chronic daily intake (CDI) and hazard quotient (HQ) during both seasons were in the order Ca > Na > HCO 3  > Cl > CO 3  > SO 4  > Mg > NO 3  > K > F and was as well computed. Conclusion The significant reasons for water quality degrading in the study area were associated with various natural and anthropogenic sources and their unsystematic apportionment, show that proper land uses, industrial planning, design some remedial techniques and implementation of existing laws to have active groundwater resource management.