Automated crude oil vapor inhalation exposure system
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Automated crude oil vapor inhalation exposure system

Filetype[PDF-1.97 MB]


English

Details:

  • Alternative Title:
    Inhal Toxicol
  • Personal Author:
  • Description:
    Objective:

    Inhalation exposure systems are tools for delivering compounds (particles, vapors, and gases) under well-controlled conditions for toxicological testing. The objective of this project was to develop an automated computer-controlled system to expose small laboratory animals to precise concentrations of crude oil vapor (COV).

    Materials and Methods:

    Vapor from heated Deepwater Horizon surrogate oil was atomized into a fine mist then diluted with filtered air, then the air/droplet mixture was routed into an evaporation column with an high efficiency particulate air (HEPA) filter on its exit port. The HEPA filter was used to remove oil particles, thus ensuring only vapor would pass. The vapor was then introduced into a custom-built exposure chamber housing rats. A calibrated flame ionization detector was used to read the total volatile organic compounds (TVOC) in real time, and custom software was developed to automatically adjust the amount of oil entering the atomizer with a syringe pump. The software also controlled relative humidity and pressure inside the exposure chamber. Other exposure chamber environmental parameters, e.g. temperature and CO2 levels, were monitored. Four specific components within the COV were monitored during each exposure: benzene, toluene, ethylbenzene, and xylenes.

    Results:

    The TVOC vapor concentration control algorithm maintained median concentrations to within ±2 ppm of the target concentration (300 ppm) of TVOC during exposures lasting 6 h. The system could reach 90% of the desired target in less than 15 min, and repeat exposures were consistent and reproducible.

    Conclusion:

    This exposure system provided a highly automated tool for conducting COV inhalation toxicology studies.

  • Subjects:
  • Source:
  • Pubmed ID:
    36007004
  • Pubmed Central ID:
    PMC9876599
  • Document Type:
  • Funding:
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