IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v6y2009i2p622-634d3962.html
   My bibliography  Save this article

Application of Bayesian Methods to Exposure Assessment of Area Concentrations at a Rubber Factory

Author

Listed:
  • Yonghua He

    (School of Public Health, Fudan University /Box 288, No 130, Dong’an Road, Shanghai 200032, PR China)

  • Youxin Liang

    (School of Public Health, Fudan University /Box 288, No 130, Dong’an Road, Shanghai 200032, PR China)

  • Hua Fu

    (School of Public Health, Fudan University /Box 288, No 130, Dong’an Road, Shanghai 200032, PR China)

Abstract

The present study estimated area concentrations of airborne benzene in several workshops using Bayesian methods based on available historical measurements. A rubber products factory utilizing benzene was investigated. Historical measurements of benzene concentrations, expert experiences, and deterministic modeling were utilized in a Bayesian Method to estimate area concentrations. Historical concentrations (n=124) were available with the geometric mean of 15.3 mg/m 3 . The geometric mean of the current field measurements on the workstations ranged from 0.7 to 89.0 mg/m 3 . One of the seven historical geometric means by work locations significantly differed from the field measurements for equivalent locations, but none of the geometric means of Bayesian estimates were significantly different from the field measurement results. The Bayesian methods based on the historical measurements appeared to be a useful tool for more closely estimating area concentrations shown by field data than that predicted only using historical measurements.

Suggested Citation

  • Yonghua He & Youxin Liang & Hua Fu, 2009. "Application of Bayesian Methods to Exposure Assessment of Area Concentrations at a Rubber Factory," IJERPH, MDPI, vol. 6(2), pages 1-13, February.
  • Handle: RePEc:gam:jijerp:v:6:y:2009:i:2:p:622-634:d:3962
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/6/2/622/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/6/2/622/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:6:y:2009:i:2:p:622-634:d:3962. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.