PubMed · 10772017
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B Busby. 2000. Uranium.. https://doi.org/10.1097/00004032-200005000-00001
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The dose rate conversion factors D(CF) (absorbed dose rate in air per unit activity per unit of soil mass, nGy h(-1) per Bq kg(-1)) are calculated 1 m above ground for photon emitters of natural radionuclides uniformly distributed in the soil. Three Monte Carlo codes are used: 1) The MCNP code of Los Alamos; 2) The GEANT code of CERN; and 3) a Monte Carlo code developed in the Nuclear Technology Laboratory of the Aristotle University of Thessaloniki. The accuracy of the Monte Carlo results is tested by the comparison of the unscattered flux obtained by the three Monte Carlo codes with an independent straightforward calculation. All codes and particularly the MCNP calculate accurately the absorbed dose rate in air due to the unscattered radiation. For the total radiation (unscattered plus scattered) the D(CF) values calculated from the three codes are in very good agreement between them. The comparison between these results and the results deduced previously by other authors indicates a good agreement (less than 15% of difference) for photon energies above 1,500 keV. Antithetically, the agreement is not as good (difference of 20-30%) for the low energy photons.
The BEIR-VI Report suggests that the large discrepancy between the observed lung cancer rate vs. radon exposure relationship for U.S. counties, and the predictions of linear no-threshold theory, may be explained by a strong negative correlation between smoking intensity and radon exposure. It proposes a model for testing that suggestion. We apply that model to the detailed data for U.S. counties; analysis shows that even a perfect negative correlation explains little more than half of the discrepancy, and the largest not-implausible correlation can explain less than a quarter of the discrepancy. We then extend the BEIR-VI suggestion to include a strong negative correlation between both the prevalence of smoking and the intensity of smoking. The largest not-implausible correlations can explain no more than 30% of the discrepancy. It is concluded that the previous interpretation of these data, that linear no-threshold theory fails this test, is sustained.