Relationship between geosorbent properties and field-based partition coefficients for pesticides in surface water and sediments of selected agrarian catchments: Implications for risk assessment

2018 
Abstract Studies on pesticide behavior, adsorption-likelihood, and bioavailability vis-a-vis geosorbent properties and seasons, are critical for understanding pesticide-fate and risks in pesticide-prone environments. We examined the relationship between geosorbent profiles of sediments (percentage sand, silt, clay, organic carbon content) across seasons and occurrence of pesticide residues in surface water and sediment of agricultural catchments at Owan, Ogbesse and Illushi communities of Edo State, Nigeria. Pesticide concentrations were measured monthly in samples of surface water and sediments across the selected sites for 18-months. Pesticide behavior and sorption-likelihoods were examined using partition coefficients K d (sediment-water coefficient), K oc (sediment-water coefficient normalized for organic carbon) and Log K ow (octane-water coefficient); the relationship between K d and K oc was also examined. Results of the principal component analysis (PCA) indicated that pesticide levels in sediment and surface water were positively associated with the rainy season, total organic content (TOC), percentage silt and clay in sediment. Field-derived pesticide partition coefficients (K d oc ow indicate that organochlorines including DDT, dieldrin, endrin and heptachlor epoxide portend significant bioaccumulation risks to humans and biota across sites. The relationship between K d and K oc for each site fitted into a quadratic model; it depicted a biphasic behavior of pesticide adsorption and desorption to sediments revealing that concentration of organic carbon across study sites was a limiting factor determining the extent of pesticide adsorption. This study demonstrates that understanding pesticide mobility using field-based partition coefficients could give a clearer picture of pesticide risks to biota and human populations.
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