Age-dependent doses to members of the public from intake of radionuclides Part 4: Inhalation dose coefficients

https://stacks.cdc.gov/view/cdc/37676/cdc_37676_DS1.pdf

Toxicological Profile for Lead

http://www.pebblescience.org/Pebble-Mine/acid-drainage-pdfs/MetalsRiskAssessmentEPA07.pdf

Framework for metals risk assessment.

Properties and behaviour of radon and thoron and their decay products in the air

Influence of particle size on regional lung deposition - What evidence is there?

A general algorithm for solving first-order compartmental models including recycling systems has been developed and its implementation on a microcomputer is described. Matrix algebra is used to obtain for any compartmental model an analytical solution, which is expressed as the exponential of a matrix of rate constants. A special technique is used in the algorithm to enable this exponential to be evaluated with a rapidly converging series. Truncation errors incurred in this process are estimated automatically. Thus, in an extreme case, where these errors may be significant, the appropriate action can be taken. Given a particular model, the user enters the model parameters into a rate matrix according to a simple rule. The algorithm then uses this matrix to solve the model, and thus no specialized mathematical knowledge is needed. The algorithm is given in a short BASIC program (60 lines) listed in an appendix. No additional software is required. By running this program on a standard microcomputer, the user can solve models of any complexity: those up to 15 compartments in seconds and those up to 30 compartments within a minute. The algorithm is thus ideally suited to solve kinetic models describing the transport of radionuclides in the environment or the translocation of elements in biological systems such as the metabolic models recommended by the International Commission on Radiological Protection (ICRP). Given the initial amount of material in each compartment at time t = 0, together with its radioactive decay constant, the algorithm gives both the amount in each compartment at any future time t and the number of disintegrations that will have occurred in each compartment up to time t. The computer program, shown in an appendix, could easily be used to calculate disintegrations over any time interval of interest, or to predict the quantities or fractions of an intake expected to be present in any in vivo or excretion compartments of interest. Thus, the algorithm can be useful in both the design and conduct of bioassay and internal dose assessment procedures.

A microcomputer algorithm for solving first-order compartmental models involving recycling.

A parameter uncertainty analysis has been performed to derive the probability distribution of the weighted equivalent dose to lung for an adult (w lung H lung ) per unit exposure to radon progeny in the home. The analysis was performed using the ICRP Publication 66 human respiratory tract model (HRTM) with tissue weighting factor for the lung, w lung = 0.12 and the radiation weighting factor for alpha particles, w R = 20. It is assumed that the HRTM is a realistic representation of the physical and biological processes, and that the parameter values are uncertain. The parameter probability distributions used in the analysis were based on a combination of experimental results and expert judgement from several prominent European scientists. The assignment of the probability distributions describing the uncertainty in the values of the assigned fractions (A BB , A bb , A AI ) of the tissue weighting factor proved difficult in practice due to lack of quantitative data. Because of this several distributions were considered. The results of the analysis give a mean value of w lang H lung per unit exposure to radon progeny in the home of 15 mSv per working level month (WLM) for a population. For a given radon gas concentration, the mean value of w lung H lung per unit exposure is 13 mSv per 200 Bq.m -3 .y of 222 Rn. Parameters characterising the distributions of w lung H lung per unit exposure are given. If the ICRP weighting factors are fixed at their default values (A BB , A bb , A AI = 0.333, 0.333, 0.333; w lung = 0.12; and w r = 20) then on the basis of this uncertainty analysis it is extremely unlikely (P 0.0007) that a value of H w /P p for exposure in the home is as lots as 4 mSv per WLM, the value determined with the epidemiological approach. Even when the uncertainties in the A BB , A bb , A AI values are included then this probability is predicted to be between 0.01 to 0.08 depending upon the distribution assumed for describing the uncertainties in the A BB , A bb , A AI values. Thus, it is concluded that the uncertainties in the HRTM parameters considered in this study cannot totally account for the discrepancy between the dosimetric and epidemiological approaches.

Uncertainty Analysis of the Weighted Equivalent Lung Dose per Unit Exposure to Radon Progeny in the Home

This paper presents a novel Monte Carlo method (WeLMoS, Weighted Likelihood Monte-Carlo sampling method) that has been developed to perform Bayesian analyses of monitoring data. The WeLMoS method randomly samples parameters from continuous prior probability distributions and then weights each vector by its likelihood (i.e. its goodness of fit to the measurement data). Furthermore, in order to quality assure the method, and assess its strengths and weaknesses, a second method (MCMC, Markov chain Monte Carlo) has also been developed. The MCMC method uses the Metropolis algorithm to sample directly from the posterior distribution of parameters. The methods are evaluated and compared using an artificially generated case involving an exposure to a plutonium nitrate aerosol. In addition to calculating the uncertainty on internal dose, the methods can also calculate the probability distribution of model parameter values given the observed data. In other words, the techniques provide a powerful tool to obtain the estimates of parameter values that best fit the data and the associated uncertainty on these estimates. Current applications of the methodology, including the determination of lung solubility parameters, from volunteer and cohort data, are also discussed.

A Monte Carlo method for calculating Bayesian uncertainties in internal dosimetry.

The European project Alpha-Risk aims to quantify the cancer and non-cancer risks associated with multiple chronic radiation exposures by epidemiological studies, organ dose calculation and risk assessment. In the framework of this project, mathematical models have been applied to the organ dosimetry of uranium miners who are internally exposed to radon and its progeny as well as to long-lived radionuclides present in the uranium ore. This paper describes the methodology and the dosimetric models used to calculate the absorbed doses to specific organs arising from exposure to radon and its progeny in the uranium mines. The results of dose calculations are also presented.

Dosimetric models used in the Alpha-Risk project to quantify exposure of uranium miners to radon gas and its progeny.

In 1997, a collaboration between British Nuclear Fuels plc (BNFL), Westlakes Research Institute and NRPB started, with the aim of producing IMBA (Integrated Modules for Bioassay Analysis), a suite of software modules that implement the new ICRP models for estimation of intakes and doses This was partly in response to new UK regulations, and partly due to the requirement for a unified approach in estimating intakes and doses from bioassay measurements within the UK Over the past 5 years, the IMBA modules have been developed further, have gone through extensive quality assurance, and are now used for routine dose assessment by approved dosimetry services throughout the UK More recently, interest in the IMBA methodology has been shown by the United States Department of Energy (USDOE), and in 2001 an ambitious project to develop a software package (IMBA Expert USDOE Edition) which would meet the requirements of all of the major USDOE sites began Interest in IMBA Expert is now being expressed in many other countries The aim of this paper is to outline the origin and evolution of the IMBA modules (the past); to describe the full capabilities of the current IMBA Expert system (the present) and to indicate possible future directions in terms of capabilities and availability (the future)

A. Birchall

Papers

A microcomputer algorithm for solving first-order compartmental models involving recycling.

Uncertainty Analysis of the Weighted Equivalent Lung Dose per Unit Exposure to Radon Progeny in the Home

A Monte Carlo method for calculating Bayesian uncertainties in internal dosimetry.

Dosimetric models used in the Alpha-Risk project to quantify exposure of uranium miners to radon gas and its progeny.

IMBA Expert: internal dosimetry made simple.