|Abstract Title:||Rapid measurement of FOG (Fat, Oil and Grease) from waste-water using bench-top NMR|
|Presenter Name:||Dr Kevin Nott|
|Co-authors:||Dr Alexander Sagidullin|
|Company/Organisation:||Oxford Instruments Magnetic Resonance|
Abstract Information :
Measurement of Fats, Oils and Grease (FOG) in waste water is a crucial parameter in water quality control and environmental monitoring performed by water suppliers laboratories and environmental authorities. Traditionally this is carried out by passing a volume of water through a filter which collects both FOG and solid particulates; after drying the filter, the FOG is determined by Soxhlet analysis. However the Soxhlet method is a long and laborious process, requires skilled operators and the use of hazardous solvents which need to be disposed of. Furthermore, the method is not very accurate or sensitive, and the solvents that are used today are unlikely to extract all the FOG; the original chlorinated solvents used are now banned by the Montreal protocol. In contrast, bench-top, or time domain, NMR is rapid, accurate and solvent-free.
The MQC+ bench-top NMR analyser was calibrated using a set of standards prepared gravimetrically by applying known amounts of vegetable/mineral oil mixtures to filter papers. Subsequently various dried filter samples were measured by NMR and then by Soxhlet for comparison; this is possible because the NMR technique is non-destructive. In general, the results showed that NMR gives higher results and therefore is likely to be more accurate than Soxhlet analysis which is unable to measure all the FOG. In addition the NMR measurement repeatability is good.
In conclusion, the sensitivity of the NMR method enables accurate measurements of grease /oil content on a single filter sheet. In common with the Soxhlet method, the samples have to be dried overnight. No additional preparation is required apart from sample conditioning at 40°C to mobilise the FOG for NMR analysis, and a single sample measurement is rapid (typically 5 minutes). After conditioning, the samples can be measured in batches which is amenable to automation.