Thomas G. Hinton
Savannah River Ecology Laboratory
P O Drawer E, Aiken, SC 29802
(803) 725-7454 office
(803) 725-3309 fax
Because the culmination of radioecological research is in the prediction of effects to humans and the environment, an important part of Dr. Hinton's research program is directed towards human and ecological risk analyses. He has published several manuscripts and two chapters on risks from exposure to radiation. Most recently, he has served as a consultant for the International Atomic Energy Agency (IAEA) and helped develop a synopsis on the ecological effects of the Chernobyl accident (Fig. 3).
|Figure 3. The changing radiological conditions with time following the Chernobyl accident can be grouped into three time periods, with the largest doses to biota occurring within the first month. Rapid decreases in dose were due to decay of short-lived radionuclides and migration of contaminants into deeper soil layers (from IAEA synopsis, in press).|
Heightened interests in the effects of radiation on non-human biota is occurring because of the 20th anniversary of the Chernobyl accident (April 1986), and an international interest in developing regulations that specifically protect non-human biota. The latter is a shift in the long-standing paradigm that if humans are adequately protected from ionizing radiation then so are all other biota, and that specific regulations for non-human biota are not needed. The International Commission of Radiological Protection, the IAEA, and several national organizations in various countries, including the U.S. Department of Energy (DOE), are proposing new approaches for specifically determining radiological risks to exposed biota. Dr. Hinton is actively involved in this international debate and has authored several papers on the subject.
An example of Hinton's contribution to risk- related research centers on the current international guidance for protection of the environment from ionizing radiation. It argues that populations of biota are adequately protected if dose rates to the maximally exposed individual are below a certain limit. Based on data sampled from natural populations, resource managers need to be able to test the hypothesis that dose to the maximally exposed individual is acceptable. Recognizing the difficulty of sampling the maximally exposed individual within a contaminated environment, risk assessors have used various alternative approaches that vary from changing the paradigm and applying recommended dose rate limits to representatively, rather than maximally exposed individuals, to using the 95th percentile of the sample mean as an estimator of the population maximum. To determine the effectiveness of numerous proposed alternatives, Dr. Hinton, in collaboration with Dr. Machelle Wilson (University of Georgia), used computer simulation techniques to generate a "population" of doses with known distributional qualities, and then mathematically "sampled" the population to compare the ability of the various statistics at estimating the population maximum.. Their approach allowed them to quantify the bias associated with several approaches used to determine compliance with dose rate criteria established by the Department of Energy for protecting biota. Their results suggest shifting the regulatory criterion appropriately to argue that if the top 1% (as opposed to the maximum) of the population has a dose rate less than or equal to the regulatory limit, then the population is adequately protected, and then using the maximum likelihood estimate of the 99th percentile as the least biased sample statistic (Fig. 4). Results from this line of research are also relevant when estimating dose to critical subgroups of humans whose lifestyles are such that their doses are among the maximum for the population.
|Figure 4. Histograms of 1000 model simulations derived from a log-normally distributed population of fish prey. The maximum likelihood estimate of the 99.99th percentile (MLE), the sample maximum (SampMax), and the 95th percentile of the sample mean (Mean95Q) are compared to the population maximum (PopMax). The histograms in Fig. A were based on a sample size of 52. Histograms in Fig. B show the impact of reducing the sample size from 52 to 20; and the histograms presented in Fig. C are when a false assumption is made and the distribution of the population is incorrectly assumed to be normally distributed rather than log-normally.|
To better understand the effects of chronic exposures from ionizing radiation on biota, Dr. Hinton designed, constructed and manages a unique Low Dose-Rate Irradiation Facility. No other facility in the world exists where such chronic low dose-rate irradiation can be administered to large numbers of animals in a controlled and replicated manner.