Olfactory characterisation of odours for optimising impact assessment

ARC Discovery (2010-2012): Prof Richard Stuetz, Dr Kate Murphy and Prof Ramus Bro

Project funding: $330,000

Complaints due to odour annoyance have become a major issue for intensive livestock, waste management and wastewater treatment operators. Odour assessment which uses dilution olfactometry does not take into account odour quality or intensity, both important aspects for predicting olfactory impact. This project will apply a range of exploratory and predictive statistical tools in order to summarize relationships between olfactory and chemical data obtained in the field. Our goal is to characterise odorous emissions and develop relationships between the dominant odorants and chemical composition at different stages of industrial processes.

In the first phase of the project, chemometric models are being used to separate and purify signals from volatile organic compounds (VOCs) that have been measured using GC-MS gas chromatography, including PArallel FACtor Analysis (PARAFAC) and multivariate curve resolution (MCR). The purified profiles are compared with the NIST spectral database, in order to identify which VOCs are present. We are working with the developer of the open source software, OpenChrom, to develop an interface between GC-MS models and NIST, to make this process simpler and faster.

In latter phases of the project, VOCs will be correlated with olfactory data, with the aim of discovering which VOCs are responsible for nuisance odours. Since it is easier to measure VOCs than it is to measure odours, we wish to develop robust models that can use VOC data to predict when odour problems are likely to occur.  

Research Staff: Dr Kate Murphy, ARC Post-doctoral Fellow (2010-2013).