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Toward Developing a New Occupational Exposure Metric Approach for Characterization of Diesel Aerosols

Filetype[PDF-568.83 KB]


  • English

  • Details:

    • Alternative Title:
      Aerosol Sci Technol
    • Description:
      The extensive use of diesel-powered equipment in mines makes the exposure to diesel aerosols a serious occupational issue. The exposure metric currently used in U.S. underground noncoal mines is based on the measurement of total carbon (TC) and elemental carbon (EC) mass concentration in the air. Recent toxicological evidence suggests that the measurement of mass concentration is not sufficient to correlate ultrafine aerosol exposure with health effects. This urges the evaluation of alternative measurements. In this study, the current exposure metric and two additional metrics, the surface area and the total number concentration, were evaluated by conducting simultaneous measurements of diesel ultrafine aerosols in a laboratory setting. The results showed that the surface area and total number concentration of the particles per unit of mass varied substantially with the engine operating condition. The specific surface area (SSA) and specific number concentration (SNC) normalized with TC varied two and five times, respectively. This implies that miners, whose exposure is measured only as TC, might be exposed to an unknown variable number concentration of diesel particles and commensurate particle surface area. Taken separately, mass, surface area, and number concentration did not completely characterize the aerosols. A comprehensive assessment of diesel aerosol exposure should include all of these elements, but the use of laboratory instruments in underground mines is generally impracticable. The article proposes a new approach to solve this problem. Using SSA and SNC calculated from field-type measurements, the evaluation of additional physical properties can be obtained by using the proposed approach.
    • Pubmed ID:
      26361400
    • Pubmed Central ID:
      PMC4562385
    • Document Type:
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