Abstract

In the context of increasing uses of Arsenic contaminated groundwater for irrigation in Bangladesh and observed health related problems, we evaluated potential health risk for Bangladesh is due to As exposure from consumption of vegetables. Eight vegetable plants (Amaranth, Arum, Carrot, Eggplant, Indian Spinach, Okra, Potato and Radish) were grown in open field and irrigated with natural As contaminated water (0.005-0.903 mg L-1) for 80-90 days. The average As concentrations in the vegetables, measured by GF-AAS, were 0.431, 0.719, 0.928, 1.574 and 2.287 mg kg-1 (ww.) corresponding to irrigation water As concentrations of 0.005 (control), 0.044, 0.103, 0.507 and 0.903 mg L-1 respectively. We established linear regression equation of fitted model for water-vegetable As concentration (n=54) relationship (r=0.767 and P<0.05). Statistical analyses with r value, P value of ANOVA table, Durbin-Watson Statistic and Lack-of-Fit test strongly validated the model. Merging British Geological Survey’s (BGS) groundwater datasets (n=3534) for Bangladesh to the model led to estimation of As concentrations in vegetables district-wise. We followed USEPA Guidelines for Exposure Assessment for evaluation of human health risk. Risk, defined as ‘Hazard Quotient’ (HQ), was mapped for three vulnerable population sub-groups: Highly Exposed Child, Average Person and Senior. The results showed that all the children (0-6 years) were at health risk, whereas 98% of seniors and 76% of average persons (i.e., adults) were safe in consuming vegetables. The eight administrative division-wise HQ values for average persons were as follows: Rangpur (0.760)<Rajshahi (0.775)<Mymensingh (0.805)<Barisal (0.815)<Sylhet (0.820)<Khulna (0.990)<Dhaka (0.996)<Chittagong (1.147). The worst affected district was Chandpur. The findings explored the extent of As health risk for children (0-6 years), adults and seniors of Bangladesh precisely from vegetable consumption. This study highlights the importance of sight-specific risk assessment considering more pollutant parameters.

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