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Odour is a property of a mixture of different volatile chemical species (sulphur, nitrogen, and volatile organic compounds) capable of stimulating the olfaction sense sufficiently to trigger a sensation of odour. The impact of odours on the surrounding areas depends on different factors, such as the amount of odours emitted from the source, the distance from the source, weather conditions, topography, odours sensitivity and tolerance of the neighbourhood. Due to the complexity of the odour issue, the aim of this project was to give an overview of techniques (sensorial and analytical) that can be used to determine a qualitative and quantitative characterisation of odour emissions in oil refineries.

A very limited number of reports discussing the use of dispersion models in experiments with intensely odourous substances for model validation purposes can be found in literature. How-ever, in the case of odour emissions, it is not always possible to identify the exact traces of odourous compounds, nor to find a link between their analytical concentrations and odour properties. From this point of view, the consideration of individual odourous compounds may not be sufficient to account for the effective perception of the odour obtained. This article aims to review the applied dispersion models that are accepted for estimating the emission of odours in order to assess their impact, as well as how the results of measurements of odours obtained at a particular place and the results of the model can be compared and compared each other. Most odour emission management strategies include measures and specific developed management plans designed to prevent, control, disperse, minimise nuisance or eliminate odour emissions.

The performance of the commercial LUKOIL Neftohim Burgas fluid catalytic cracking unit (LNB FCCU) during processing 24 blends of straight run vacuum gas oils originating from 16 petroleum crudes and an imported atmospheric residue and employment of four catalysts was evaluated. It was found that the nature of the petroleum crudes processed in the ratios employed had no effect on the LNB FCCU performance. Instead, the content of the H-Oil vacuum gas oil (VGO) and its quality quantified by Kw-characterization factor was found to control the LNB FCCU conversion level. Based on the LNB FCCU commercial data a regression was developed quantifying the effect of equilibrium catalyst activity, H-Oil quality, and quantity in the fluid catalytic cracking (FCC) feed, and catalyst-to-oil ratio on the level of conversion. The regression was used to evaluate the impact of catalyst activity and catalyst-to-oil ratio, that is known to be a function of catalyst Δ coke selectivity, on the FCC conversion.