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Predicting New Hampshire indoor radon concentrations from geologic information and other covariates
Authors:M G Apte  P N Price  A V Nero  K L Revzan
Institution:(1) Ernest Orlando Lawrence Berkeley Laboratory, Energy and Environment Division, University of California, Berkeley, CA 94720 Fax: +1 510 486 6658 e-mail: pnprice@lbl.gov,
Abstract: Generalized geologic province information and data on house construction were used to predict indoor radon concentrations in New Hampshire (NH). A mixed-effects regression model was used to predict the geometric mean (GM) short-term radon concentrations in 259 NH towns. Bayesian methods were used to avoid over-fitting and to minimize the effects of small sample variation within towns. Data from a random survey of short-term radon measurements, individual residence building characteristics, along with geologic unit information, and average surface radium concentration by town, were variables used in the model. Predicted town GM short-term indoor radon concentrations for detached houses with usable basements range from 34 Bq/m3 (1 pCi/l) to 558 Bq/m3 (15 pCi/l), with uncertainties of about 30%. A geologic province consisting of glacial deposits and marine sediments was associated with significantly elevated radon levels, after adjustment for radium concentration and building type. Validation and interpretation of results are discussed. Received: 20 October 1997 · Accepted: 18 May 1998
Keywords:  Radon  Bayesian statistics
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