title: On the replacement of empirical parameters in multimedia mass balance models with QSPR data.
abstract: Official OECD recommendations give the highest priority to application of purely empirical phys/chem data (partition coefficients, environmental half-live times etc.) in multimedia mass balance modeling of environmental overall persistence and long-range transport for potentially hazardous chemicals. We have demonstrated that the replacement of the empirical data with those predicted by employing Quantitative Structure-Property Relationships (QSPR) technique did not significantly decrease the performance of The Tool 2.0--the OECD multimedia mass balance model. To prove this, we compared each other the output results (overall persistence -P(OV); characteristic traveling distance -CTD and transport efficiency TE) obtained from 6 of multimedia models. The models utilized combinations of experimentally determined and QSPR-predicted values of the partition coefficients and half-live times. For predicting phys/chem data, we utilized 2 QSPRs developed in our laboratory and the EPI Suite package (US EPA). We did not observe any statistically significant (p<0.05) differences between the models. This conclusion is important, because it leads to reducing time and costs of laboratory studies required during the risk assessment procedure. Moreover, regarding the obtained results, we proposed to replace the single-threshold approaches established by majority of international regulations to screen substances for persistence, bioaccumulation and long-range transport potential with the approaches taking into account uncertainty of the results and/or probability of passing a given threshold.
authors: Faculty of Chemistry, Laboratory of Environmental Chemometrics, University of Gdansk, ul Sobieskiego 18/19, 80-952 Gdansk, Poland. t.puzyn@qsar.eu.org
authors: Tomasz
authors: T
authors: Puzyn
mesh_terms: D002623:Chemistry Techniques, Analytical; D002627:Chemistry, Physical / Q000379:methods; D003627:Data Interpretation, Statistical; D004784:Environmental Monitoring / Q000379:methods; D017143:Fuzzy Logic; D015386:Hazardous Substances / Q000032:analysis; D007700:Kinetics; D008956:Models, Chemical; D008962:Models, Theoretical; D011336:Probability; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D015386:Hazardous Substances