LAUSR

Existing Chemical Substances of China (IECSC) that highlighted some lesser-known organosilicons via an in-silico screening. They contended that the screening results of organosilicon compounds were highly uncertain because (1) the tools we used to generate physicochemical properties and environmental fate data are not suitable for organosilicon substances; (2) some environmental transformation processes such as hydrolysis were not considered, and (3) the in silico model was overly simplistic. Here we provide our responses to the comments. Based on our screening and additional weight of evidence, we highlight some organosilicons produced in China that deserve further environmental research. Due to the large number of chemicals currently used in commerce, risk assessors often adopt a tiered approach for evaluating potential hazards. High-throughput screening is first used to identify and prioritize chemicals that require more indepth investigations and assessments. The objective of our study was to perform a first-tier assessment and select chemicals in the IECSC that have environmental fate and partitioning behavior similar to that of persistent organic pollutants (POPs). Due to large data gaps, chemical assessments at this stage, including our study, involve estimated values, simplifications and assumptions based on weight of evidence and the precautionary principle. For example, octanol is often used as a proxy for organic matter complexation in soil and sediment, and is a well-established model simplification, given the paucity of measurements for many chemicals on water−soil partitioning. When no data are available for processes such as hydrolysis, a precautionary assumption is often that the transformation does not contribute to the loss of chemicals. While it is recognized to take a conservative approach, the value of in-silico screening for identifying POP-like chemicals, including organosilicons, is well-established by previous work using approaches similar to ours. It is particularly important to avoid false negatives as false positives can be identified/ruled out by more in-depth analysis. In our paper, we acknowledged the uncertainty inherent in such screening results that originate from the nature of quantitative structure−property relationships (QSPRs) and environmental fate models. We excluded chemicals for which the QSPRs are unsuitable (Table S8 of Zhang et al.) and discussed the general uncertainty involved in our screening results. We agree with Guerrero and Thomas that greater uncertainty may exist in QSPR predicted properties of organosilicons compared to other neutral organics. Available measured physicochemical properties and environmental fate data are limited to a few linear and cyclic volatile methylsiloxanes and therefore the training data set for QSPRs does not comprehensively cover the diverse structures of organosilicons. Nevertheless, the use of EPISuite (v4.11− 2012) for organosiloxanes has been justified in a review by Rücker and Kümmerer. Specifically, these authors highlight that (1) the training set includes organosilicons and (2) the discrepancies between the predicted physicochemical properties and available measurements are not significantly higher than those between different measurements (1 for log octanol−water partition coefficient (KOW) and 1.5 for log air−water partition coefficient (KAW)). Further, EPISuite Figure 1. Comparisons of measured logKOW and logKOA values of organosilicons with EPISuite predicted values (v4.11 before and after the update in 2017 that added additional data of organosilicons for the model training). Correspondence/Rebuttal pubs.acs.org/est