Strategies to Reduce Uncertainties from the Best Available Physicochemical Parameters Used for Modeling Novel Organophosphate Esters across Multimedia Environments

Abstract

Organophosphate esters (OPEs) raise growing environmental and human health concerns globally. However, numerous novel OPEs lack data on physicochemical properties, which are essential for assessing environmental fate, exposure, and risks. This study predicted water solubility (S_w), vapor pressure (V_p), octanol–water partition coefficient (K_ow), and octanol–air partition coefficient (K_oa) at 25 °C for 46 novel OPEs by identifying optimal in silico tools and establishing prediction strategies based on molecular weights (MWs). Prediction discrepancies between in silico tools increased with MWs and structural complexity. Method evaluations for compounds with MWs > 450 g/mol suggest that COSMOtherm is advantageous in predicting S_w and V_p for alkyl-OPEs, while SPARC is better for predicting V_p for aryl- and halogenated-OPEs. For compounds with MWs > 500 g/mol, COSMOtherm and SPARC are recommended for K_ow and K_oa prediction, respectively. For smaller OPEs, average values from the top three of COSMOtherm, SPARC, EPI Suite, and OPERA, ranked by validation on traditional flame retardants, are recommended. Using improper software could cause deviations in multimedia distribution and overall persistence in the environment by up to 83 and 350%, respectively. The present data and prediction strategy are useful to enhance the reliability of environmental fate, exposure, and risk assessments of various OPEs and emerging contaminants.