1 School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
2 The Key Laboratory of Environmental Health Impact Assessment for Emerging Pollutants, Ministry of Ecology and Environment of the People's Republic of China, Shanghai 200240, China.
3 Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China.
4 Department of Chemistry and Biochemistry, Concordia University, 7141 Sherbrooke Street West, Montreal, Quebec H4B 1R6, Canada.
5 Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom.

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.