title: Evaluation of a novel high throughput screening tool for relative emissions of industrial chemicals used in chemical products.
abstract: Tens of thousands of chemicals are currently marketed worldwide, but only a small number of these compounds has been measured in effluents or the environment to date. The need for screening methodologies to select candidates for environmental monitoring is therefore significant. To meet this need, the Swedish Chemicals Agency developed the Exposure Index (EI), a model for ranking emissions to a number of environmental matrices based on chemical quantity used and use pattern. Here we evaluate the EI. Data on measured concentrations of organic chemicals in sewage treatment plants, one of the recipients considered in the EI model, were compiled from the literature, and the correlation between predicted emission levels and observed concentrations was assessed by linear regression analysis. The adequacy of the parameters employed in the EI was further explored by calibration of the model to measured concentrations. The EI was found to be of limited use for ranking contaminant levels in STPs; the r² values for the regressions between predicted and observed values ranged from 0.02 (p = 0.243) to 0.14 (p = 0.007) depending on the dataset. The calibrated version of the model produced only slightly better predictions although it was fitted to the experimental data. However, the model is a valuable first step in developing a high throughput screening tool for organic contaminants, and there is potential for improving the EI algorithm.
authors.affiliation: Department for Applied Environmental Science, Stockholm University, Sweden. emma.undeman@itm.su.se
authors.forename: Emma
authors.initials: E
authors.lastname: Undeman
authors.forename: Stellan
authors.initials: S
authors.lastname: Fischer
authors.forename: Michael S
authors.initials: MS
authors.lastname: McLachlan
mesh_terms: D004781:Environmental Exposure / Q000032:analysis / Q000706:statistics & numerical data; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods*; D007220:Industrial Waste / Q000032:analysis* / Q000706:statistics & numerical data; D016014:Linear Models; D008956:Models, Chemical; D009010:Monte Carlo Method; D009930:Organic Chemicals / Q000032:analysis* / Q000737:chemistry; D012044:Regression Analysis; D018570:Risk Assessment; D012722:Sewage / Q000737:chemistry; D014865:Waste Disposal, Fluid; D014874:Water Pollutants, Chemical / Q000032:analysis* / Q000145:classification
chemical_list: D007220:Industrial Waste; D009930:Organic Chemicals; D012722:Sewage; D014874:Water Pollutants, Chemical