Estimation of Groundwater Radon in North Carolina Using Land Use Regression and Bayesian Maximum Entropy

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• 作者：Kyle P. Messier ; Ted Campbell ; Philip J. Bradley ; Marc L. Serre
• 刊名：Environmental Science & Technology
• 出版年：2015
• 出版时间：August 18, 2015
• 年：2015
• 卷：49
• 期：16
• 页码：9817-9825
• 全文大小：488K
• ISSN：1520-5851

文摘

Radon (²²²Rn) is a naturally occurring chemically inert, colorless, and odorless radioactive gas produced from the decay of uranium (²³⁸U), which is ubiquitous in rocks and soils worldwide. Exposure to ²²²Rn is likely the second leading cause of lung cancer after cigarette smoking via inhalation; however, exposure through untreated groundwater is also a contributing factor to both inhalation and ingestion routes. A land use regression (LUR) model for groundwater ²²²Rn with anisotropic geological and ²³⁸U based explanatory variables is developed, which helps elucidate the factors contributing to elevated ²²²Rn across North Carolina. The LUR is also integrated into the Bayesian Maximum Entropy (BME) geostatistical framework to increase accuracy and produce a point-level LUR-BME model of groundwater ²²²Rn across North Carolina including prediction uncertainty. The LUR-BME model of groundwater ²²²Rn results in a leave-one out cross-validation r² of 0.46 (Pearson correlation coefficient = 0.68), effectively predicting within the spatial covariance range. Modeled results of ²²²Rn concentrations show variability among intrusive felsic geological formations likely due to average bedrock ²³⁸U defined on the basis of overlying stream-sediment ²³⁸U concentrations that is a widely distributed consistently analyzed point-source data.