Estimating measurement uncertainty for particulate emissions from stationary sources


  • G.B Woollatt LEVEGO, PO Box 422, Modderfontein, Gauteng, 1645, South Africa



uncertainty, particulate emissions, stationary sources, gum


The estimation of measurement uncertainty with regards to hazardous air pollution emissions from stationary sources is currently the most uncertain element associated with respect to obtaining relevant, valid particulate matter (PM) emission data in South Africa. This project is aimed at developing an appropriate method to evaluate the uncertainty associated with PM measurements conducted for stationary source emissions in the South African context. A series of In-Stack measurements were taken in accordance with recognized international methodology (ISO 9096:1992 and 2003) on two different industrial processes, representing a compliant and non-compliant scenario. A comparison between the two scenarios was made in an attempt to establish what components of the sampling technique have the greatest error.

The overarching goal of this project was to establish an estimate of the cumulative uncertainty on the final emission values obtained, inclusive of both analytical, field sampling and process related variables that may result in a cumulative error associated with quantifying stationary source PM emission values.

The results of the study found that the estimated combined expanded uncertainty for both sets of data was calculated to be between 62 – 72%. Upon closer analysis of the data it was ascertained that the data obtained were inadequate and the calculation of the uncertainty of the results both with the compliant and non-compliant sampling campaigns revealed that the variability of the results was too great for both scenarios to make any statistically valid observations or conclusions about the data.

In lieu of this the author has developed an alternative tool (a sampling suitability matrix) for assessing the quality and reliability of reported emission figures. It is expected to add significant value to the interpretation of the quality and reliability of the final emission results reported. 


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How to Cite

Woollatt, G. (2017). Estimating measurement uncertainty for particulate emissions from stationary sources. Clean Air Journal, 27(1), 19.



Technical Article