Odour prediction model using odour activity value from pharmaceutical industry

Data was collected from three pharmaceutical industries (two Western pharmaceutical industries and one traditional Chinese pharmaceutical industry). Odour concentration was measured by the triangular odour bag method; compounds were quantified by gas chromatography-mass spectrometry. The specific objectives were to determine which compounds contributed most to the overall odour emanating from pharmaceutical industry, and develop equations for predicting odour concentration based on compound odour activity value (OAV). OAV is defined as the concentration of a single compound divided by the odour threshold for that compound. The larger the OAV, the more likely that compound would contribute to the overall odour of a complex odour mixture. According to the OAV and regression analyses, we concluded that acetaldehyde, acetone, ethanol and NH3 were the most likely contributors to the odour in Western pharmaceutical sites. While for the traditional Chinese pharmaceutical site, acetaldehyde, acetone, H2S, methanal and ethanol were the most likely contributors to the overall odor. Acetaldehyde and Acetone were the compounds with the highest OAV from both Western and Chinese pharmaceutical industries. The multivariate regression analyse results showed that individual OAV was a good predictor of odour concentration for traditional Chinese pharmaceutical industry, the R2 of the regression equations ranged from 0.85 to 0.93. While for Western pharmaceutical industry, the odour concentration predictions was poor with R2 ranged from 0.30 to 0.65