County-level indoor radon concentration mapping and uncertainty assessment in South Korea using geostatistical simulation and environmental factors.

This paper presents a geostatistical simulation approach to not only map the county-level indoor radon concentration (IRC) distributions in South Korea, but also quantify the uncertainty that can be used as decision-supporting information. For county-level IRC mapping in South Korea, environmental factors including geology, radium concentration in surface soil, gravel content in subsoil, and fault line density, which are known to be associated with the source and migration of radon gas, were incorporated into IRC measurements using multi-Gaussian kriging with local means. These four environmental factors could account for about 36% of the variability of noise-filtered IRCs, implying that regional variations of IRCs were affected by these factors.

Geographical Correlations between Indoor Radon Concentration and Risks of Lung Cancer, Non-Hodgkin's Lymphoma, and Leukemia during 1999-2008 in Korea.

Indoor radon is the second most important risk factor for lung cancer and may also be a risk factor for hematopoietic cancers, particularly in children and adolescents. The present study measured indoor radon concentration nationwide at 5553 points during 1989-2009 and spatially interpolated using lognormal kriging. The incidences of lung cancer, non-Hodgkin's lymphoma (NHL), and leukemia, stratified by sex and five-year age groups in each of the 234 administrative regions in the country during 1999-2008, were obtained from the National Cancer Registry and used to calculate the standardized incidence ratios.

Comparison of geostatistical kriging algorithms for intertidal surface sediment facies mapping with grain size data.

This paper compares the predictive performance of different geostatistical kriging algorithms for intertidal surface sediment facies mapping using grain size data. Indicator kriging, which maps facies types from conditional probabilities of predefined facies types, is first considered. In the second approach, grain size fractions are first predicted using cokriging and the facies types are then mapped.