Thermally Induced Filter Bias in TEOM Mass Measurement
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.
 
 
Help
Clear All
i


Thermally Induced Filter Bias in TEOM Mass Measurement

Filetype[PDF-1.14 MB]



Details:

  • Description:
    Researchers at the National Institute for Occupational Safety and Health (NIOSH) have long used stationary tapered element oscillating microbalances (TEOMs®) in laboratory settings. They have served to assess the mass concentration of laboratory-generated particulates in experimental , dust chambers and they provide a reference method for comparison with other particulate- measuring instruments. Current NIOSH research is focused on further adapting TEOM technology as a wearable personal dust monitor (PDM) for coal mining occupations. This investigation's goal is to help identify, quantify, and provide means for resolving certain TEOM- related error. The present research investigated bias caused by thermal effects on filter assemblies. New filters used in the PDM for 8 h tests show an average positive bias of 25.5 pg, while similar tests of equivalent filters used in two 1400A model TEOMs show an average positive bias of 34.3 µg. The derived bias values allow correction of previously collected biased data. Also, pre- heating the filters for 24 h at 46° C shows significant bias reduction, with PDM pre-heated filters subsequently averaging -3.3 µg and 1400A TEOM filters averaging 5.9 µg. On a single-point comparison to gravimetric sampling, a 25.5 µg bias is only significant at low mass loadings. At 2.5 mg, this bias represents a negligible 1 % of the mass measurement. If ordinary linear regression is used, the bias is still insignificant. However, if the more valid weighted linear regression is used, it gives more weight to the smaller dependent variable values, which are more impacted by the bias. Consequently, what is 1% bias on a single high-mass value can translate into a larger bias percentage at high-mass values when performing a weighted regression on data that include a large number of low-mass values.
  • Subject:
  • Main Document Checksum:
  • File Type:

Supporting Files

  • No Additional Files

More +

You May Also Like

Checkout today's featured content at stacks.cdc.gov