Category Archives: Knowledge Base

Uncertainty of dustfall monitoring results

Single Bucket DustWatch unit

Let’s continue to read some of this online early research article on the “Uncertainty of dustfall monitoring results” by Martin A van Nierop, Elanie van Staden, Jared Lodder and Stuart J Piketh

To read the full article and to see any diagrams referred to below, follow this link – Clean Air Journal

To read the start of this research paper, follow this link – Fugitive Dust

Statistical analysis
The variability of each bucket at each site was calculated to determine the difference in the dust collected for each bucket by calculating the standard deviation for each sampler. This gave an indication of precision. Box plots for all of the sites for every month show the distribution of the data. A margin of error for each site was calculated using the following equation:

(1)
Where; E = margin of error
t = critical value for confidence level c (at 90%)
σ = standard deviation
n = amount of samples

To calculate the uncertainty of the results, the mean of each site was determined. The upper and lower limits (plus/minus 10% from the mean) was used to determine what percentage of samples were outside this band.

Thereafter, the relative standard deviation (%RSD) was calculated to compare the precision of the absolute deposition values between sites.
Results
Some of the results are presented in this section, the balance can be found in appendix A to C.
The standard deviation of 144 samples (12 sites monitored for 12 months) was calculated (Figure 2). 91% of the data points had a standard deviation below 400 mg/m2 /day, 81 % of the data points had a standard deviation below 300 mg/m2 /day, and 38% had standard deviations below 100 mg/m2 /day, this
gives an indication of the range of deviation for the entire data set.

The analysis of variance for the results is presented using box plots (Figures 3 and 4). These plots (representing two of the 12 months sampled) are a visual representation of the spread of
the data collected for eash site. The smaller the box plot, the lower the variance, and in this case the uncertainty.

Outliers are those data points that are statistically uncertain.

A second method of measuring the uncertainty was to plot the 90% confidence interval (Figures 5 and 6) and to determine the percentage of data points that fell outside of this interval. The majority of data points (51%) at all site fell outside of the 90% confidence level.
The third method of measuring the uncertainty was to provide a band of plus/minus 10% from the mean of the four data points and determine the number of samples lying outside of the band. This is represented graphically for sites 4 and 11 (Figures 7 and 8). 28% of the 288 results were outside the band.

Finally, the relative standard deviation is calculated to compare the precision of the absolute deposition values between sites. A high RSD value indicates a high uncertainty. The average RSD for all sites and for all months was calculated at 11.69%. Most of the sites have a low percentage RSD indicating a small spread between the points (Table 1). There are some points within the dataset that have a higher variability.
The cell shading in Table 1
represent the following:
• No colour: RSD below 15%
• Light red: RSD between 15 and 20%
• Red: RSD above 20%
• Dark Red: RSD above 40%
Discussion
Standard deviation is used to show how far the data spreads from the mean. The higher the standard deviation the more spread out the data is. A low uncertainty would be represented by a standard deviation of less than ±5% of the mean. The buckets at each site were exposed to the same environments; therefore, it is expected that they should collect the same amount of dust.
The box plots are a visual way of representing the data from the sample. It shows the minimum, maximum, median, interquartile ranges and outliers. They are only able to show the outlier with
the greatest or the smallest value. This is due to the small data groups (populations of 4). Therefore, when the area of the box is minimal, it indicated a closely spaced dataset, which in turn means precise data, i.e. lower uncertainty. Whereas a large area within the box represents spread data with large ranges between
the results, i.e. greater uncertainty. It should be considered that the amount of dust per site would vary; therefore, only the size of the box should be taken into consideration and not its position on the y-axis of the graph.

The area in which the test was conducted has a dust standard of 1,200 mg/m2 /day (NEMA: AQA, 2013). The margin of error was calculated to see if it is possible for the value of the reading to shift around this standard. That is, if the weight was just below or above the standard, would it be possible for the actual dust deposition to be above or below the standard, respectively. This confidence interval (Figures 5 and 6) indicates that for some of the samples with readings close to the standard it is possible for the result to provide a false exceedence or false conformance to the Standard.

The ASTM D1739–98 reported a standard deviation of 18% in the recovery measurements of water insoluble dustfall from Project Threshold (ASTM D1739–98. 1998), and that there was no link found between dustfall rate and reproducibility or repeatability. Repeatability and reproducibility was not conducted in this current study; however, it is aligned with the Project Threshold study. No link between the dustfall rate and repeatability (standard deviation) was found. The RSD was used to obtain an uncertainty for the entire process whereas Project Threshold reported on the laboratory component of dustfall monitoring only. The current study identifies environmental conditions that have a greater contribution to the calculated uncertainty of the method.

Conclusion:

The dustfall rate for each group of four samplers per site was expected to have a low variability given that they were exposed to the same conditions. However, variation in the dustfall rate indicates some level of uncertainty. The results of this study show that there is uncertainty in the results from the dustfall samplers. Although some uncertainty could be attributed to sample handling, the majority is considered to be from environmental factors. The proximity of the four buckets on each stand could affect the flow pattern around these buckets and potentially affect the deposition into the bucket. For this study it was assumed that the effect each bucket has on the others is equal. Future work for this study will correlate the highest mass of the four buckets with the dominant wind direction.

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Dust Monitoring Equipment – providing equipment, services and training in dust fallout management to the mining industry.

Sonic fog dust supression

Sonic fog dust supression

It always looks good as the larger dust visible dust is quickly knocked out of the air stream, which immediately wins over the process guys at a demonstration, but be aware of such miracle cures for dust problems for “The devil lies within the fine print” as it were.

The following problems are present in all such systems;

Unless the water is super clean any dust ,organic bacteria and chemical content is atomised and becomes a respirable hazard. ( The human lung is the most sensitive of all our bodily intakes) .

Any dust induced anywhere near the energy zone of the nozzles is also instantly atomised as well thus increasing the content of the dust respirable content and not reducing it which is the primary objective here as health is more important than how an area looks.

The nozzles are destroyed at an alarming rate as well even in the hardest material and respirable metal fragments are also now introduced into the air body as a further toxic agent.

Visually the largest dust particulate is suppressed quite well and one can see an immediate difference in and area.

Wind has a major effect and can simply blow the fog away before it has any chance of collecting any dust and so there is a need for larger enclosures to permit the fog to saturate the contents of the enclosures.

In almost any plant situation the generation of dust is a dynamic process and the dust is being created continuously at a rate greater than one can retain in a fixed enclosure and so the leakage is also continuous. If one is to look at a dust extraction installation then to save on wastage of air extraction one needs to enclose the chute or head end of conveyors adequately to allow the same dwell time as spoken about above, but the essential difference is that because an extraction system is extracting from the enclosure continuously there is no outward leaks as the dust being pumped into the enclosure as a volume is extracted continuously at the same volume if all your calculations are correct and your reading of the plant dynamics and the same for the material being handled are correct.

The actual real use of sonic fog is to humidify and in that regard is extensively efficient with an application mainly cooling stacks and any stack emissions to comply with environmental legislation. Ironically it is in a stack where one actually achieves a better suppression as the atmosphere up there is well away from any place where the fine particulates one is creating can cause an exposure problem.

Author:  Gerry F. Kuhn

Falout Dust 161

Single Bucket DustWatch unit

 

Analysing for various chemicals and elements in the air using Drager

Analysing for various chemicals and elements in the air using Drager

Q.  What would be the recommendation for doing the following:  (Conduct once off sampling of CO, Lead, Manganese, Mercury, Arsenic, Chromium, Nickel, Benzene, Formaldehyde, Styrene, Toluene and Tetrachloride).

 

A.  That is quite a list. As it is from an air quality report, I assume that they want it measured in the air at one or more locations. Units of measurement mg/m3 or parts per million in the air (ppm)

None of these can be determined from the fallout dust samples. It is possible to do elemental analysis on the dust to determine the Lead, Manganese, Mercury, Arsenic, Chromium, and Nickel concentrations but this will not meet the requirements or recommendations of the report as the results are given in parts per million or ppm or mass concentration, mg/kg.

My recommendation would be to research how to measure the airborne quantity of each of those chemicals and elements and then do the tests internally following the procedures.

Drager would be my starting point – http://www.draeger.com

Some of the test could be done using tubes from Drager. The tests that cannot be done in this way would then be done in other ways.

From my experience Drager have a list of chemicals that can be tested for using their pump, and the results are very useful to provide an indication of elevated levels if there are any.

By searching google for drager detection selection you will be able to download the pdf that contains the detection selection that Drager offers and if you Google Drager tube handbook then you will be able to download the handbook if required.

 

Please contact us regarding any queries.

DustWatch CC – Precipitant Dust Monitoring
082 875 0209 or 021 785 6999 (Chris)
083 308 4764 (Gerry)
0866 181 421 (Fax)
www.dustwatch.com

 

 

 

Insects and Locusts in fallout dust buckets

Insects and Locusts in fallout dust buckets

Insects and locusts can contaminate fallout dust buckets, especially in swarm or high concentrations of the insects. The strainer used during filtering will remove these from the sample but depending on how long the insect was in the bucket, the water may be further contaminated, making the processing of the sample more difficult, and in some cases the sample will have to be discarded.

Potential solutions are a mesh placed over the top of the bucket. Research into the impact of this has not been published yet, but the logic says that the dust will collect on the mesh and not land in the bucket. The mesh may also impact on the aerodynamics over the lip of the bucket causing more or less dust to be collected. Our initial assumption would be that more dust is collected in this situation.

Please contact us regarding any queries, comments, or suggestions www.dustwatch.com

Fallout Dust Monitoring and SANAS accreditation

DustWatch cc specialises in fallout dust monitoring and will be able to supply the fallout dust equipment, and laboratory equipment required to operate a fallout dust monitoring programme. We also provide training on site or in central location for people on fallout dust monitoring. SANAS accreditation for fallout dust monitoring is not feasible, especially when mines are in remote locations and doing the analysis of the samples in house. There is also no specific SANAS accreditation for just a fallout dust monitoring laboratory, so a laboratory that wants to have this accreditation must also qualify to do the other tests related to obtaining the SANAS accreditation.

Contact us for more information.

“Smoke & Water” – Fire Prevention

“Smoke & Water”

Fire Extinguisher Tutorial

Fire Extinguisher Tutorial

How to Use a Portable Fire Extinguisher Training Video

How to Use a Portable Fire Extinguisher Training Video

Transformer explosion – Fire Prevention

Transformer explosion – Fire Prevention

Educate Yourself – Teaching and Training Resources for the Geoscience Community

Teaching and Training Resources for the Geoscience Community

Check out this site for courses and free educational information on many topics.

https://www.meted.ucar.edu/

The course being focussed on at the moment is Forecasting Dust Storms Version 2.

Enjoy