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  • Title: Dealing with uncertainty in formulating occupational and public exposure limits.
    Author: Bailey WH.
    Journal: Health Phys; 2002 Sep; 83(3):402-8. PubMed ID: 12199554.
    Abstract:
    Scientists are forced to address many sources of uncertainty in the setting of exposure limits. This paper discusses the rationale for some of the approaches that have been used for many years to address uncertainties encountered in the setting of occupational and public exposure limits to protect against non-cancer effects of chemicals. These approaches are quite different from the methodology that has been adopted for the setting of exposure limits to power-frequency electric and magnetic fields to avoid adverse effects of induced electric fields and currents. The limitations of the non-standard electric and magnetic fields guideline methodology are described. To address these limitations, a probabilistic approach to developing exposure limits for electric and magnetic fields has been proposed. As a demonstration, this approach has been applied to the estimation of magnetic field exposures that would not pose significant risks of cardiac stimulation from electric fields induced in the torso. The results of this probabilistic analysis demonstrate the importance of explicitly characterizing potential sources of uncertainty and variability. Furthermore, the use of fixed, single point estimates of dosimetric parameters by electric and magnetic fields guideline-setting organizations provides more than adequate protection to individuals from the risk of cardiac stimulation. The mean magnetic field level that would increase the risk of cardiac stimulation is shown by this approach to be about three times higher than is predicted by dosimetric formulas used by the ACGIH and ICNIRP. If input data for parameters affecting the risk of adverse effects with lower thresholds, i.e., nerve stimulation, are developed and validated, this method could be used in the setting of electric and magnetic fields standards based more strongly on quantitative assessments of experimental data.
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