Recently, we reported in ES&T Letters the initial discovery of neonicotinoid insecticides and their metabolites in finished drinking water, and subsequent discovery of novel chlorinated neonic-derived disinfection byproducts. Neonicotinoids are part of a growing class of target-specific pesticides, wherein receptor binding propensity is conferred through a specific structural pharmacophore (e.g., an electronegative nitro-/cyano-group). Although neonicotinoids were not removed via conventional drinking water treatment, GAC was surprisingly effective for these high-solubility (i.e., low Kow) compounds, as demonstrated by analysis of long-term exposed spent GAC from a full scale DWTP. We hypothesized that the insecticidal pharmacophore impacted sorption to black carbon, and that removal of structurally altered neonicotinoid metabolites was inhibited. In this work, we demonstrated that neonicotinoid sorption to black carbon is extensive and largely irreversible. We characterized differences in sorption between neonicotinoid parent compounds and pharmacophore-altered products using functionalized (COOH- and NH2-) and non-functionalized carbon nanotubes and GAC. Results (just published in ES&T) indicate the electronegative pharmacophore drives sorption propensity, and presumed mechanisms likely differ between parents and products. We also evaluated the impacts of water chemistry conditions (temperature, pH, humic acid, alkalinity, ionic strength) on sorption kinetics/propensity. The hypothesized mechanisms of neonicotinoid sorption extend beyond bulk hydrophobic interactions (i.e., electrostatic and hydrogen bonding), rendering currently available prediction models (e.g., pp-LFERs/LSERs) inadequate for neonicotinoids. The lack of commercially-available authentic standards for novel transformation products led us to develop (in ongoing work) a new QSAR-based model to predict neonicotinoid partitioning using QSAR descriptors that best reflect neonicotinoid interactions that drive partitioning between octanol-water and carbon-water systems. We were able to accurately model (and externally validate) neonicotinoid partitioning, and subsequently predict partitioning of novel neonicotinoid transformation products. Our analysis provides insights as to QSAR descriptors most important for neonicotinoid partitioning, enabling more accurate predictions and illuminating new approaches for characterizing the growing class of target-specific pesticides.

Alteration of the neonicotinoid insecticidal pharmacophore drives differences in parent and product sorption: Experimental, field, and modeling results

ACS Spring Meeting 2021

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