The correct use and performance assessment of chemical fume hoods are essential to minimize operator exposure to hazardous volatile compounds. In this study, a chemometric strategy was developed to predict solvent emissions based on molecular and physicochemical descriptors. A small but representative set of solvents (ethanol, diethyl ether, isopropanol, n-hexane, and acetone) was selected according to safety profiles and structural diversity. Controlled evaporation tests were carried out using a dynamic containment setup inspired by the EN 14175 outer plane methodology. Emissions were experimentally quantified under two standardized conditions. Initially, univariate regression models were developed using Ordinary Least Squares, with vapor pressure and boiling point as single predictors. Partial Least Squares regression was therefore applied to check ten chemical–physical molecular descriptors; variable selection reduced the number to the previous two. The reduced model improves prediction accuracy under both experimental conditions, reducing the error in prediction from 4.30 to 1.48 for the first setting and from 5.25 to 3.67 for the second setting. These results demonstrate that solvent emissions from laboratory fume hoods can be reliably predicted using chemometric models based on molecular descriptors. The proposed approach offers a valuable tool for emission assessment, informed solvent selection, and chemical risk management in laboratory environments.
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