Using search-constrained inverse distance weight modeling for near real-time riverine flood modeling: Harris County, Texas, USA before, during, and after Hurricane Harvey.

Flooding poses a serious public health hazard throughout the world. Flood modeling is an important tool for emergency preparedness and response, but some common methods require a high degree of expertise or may be unworkable due to poor data quality or data availability issues. The conceptually simple method of inverse distance weight modeling offers an alternative. Using stream gauges as inputs, this study interpolated stream elevation via inverse distance weight modeling under 15 different model input parameter scenarios for Harris County, Texas, USA, from August 25th to September 15th, 2017 (before, during, and after Hurricane Harvey inundated the county). A digital elevation model was used to identify areas where modeled stream elevation exceeded ground elevation, indicating flooding. Imagery and observed high water marks were used to validate the models' outputs. There was a high degree of agreement (between 79 and 88%) between imagery and model outputs of parameterizations visually validated. Quantitative validations based on high water marks were also positive, with a Nash-Sutcliffe efficiency of in excess of .6 for all parameterizations relative to a Nash-Sutcliffe efficiency of the benchmark of 0.56. Inverse distance weight modeling offers a simple, accurate method for first-order estimations of riverine flooding in near real-time using readily available data, and outputs are robust to some alterations to input parameters.

Understanding geographic variations of indoor radon potential for comprehensive cancer control planning.

PURPOSE: Lung cancer is the leading cause of U.S. cancer deaths and radon is the second leading risk factor for lung cancer. By better understanding geologic variations of radon production in states, comprehensive cancer control efforts could be improved. The study purpose was to assess states with the greatest potential for elevated radon and the likelihood of radon-related actions in National Comprehensive Cancer Control Program (NCCCP) awardee cancer plans. METHODS: Two state-level variables were derived to approximate potential for elevated radon using the Environmental Protection Agency county map and the 2015 U.S. Census. The association between radon potential and inclusion of radon activity within cancer plans was evaluated using logistic regression. RESULTS: Fifty-one percent of cancer plans recognized an association between radon and cancer risk, and included measurable radon activities. Most states with high radon potential included radon activity in cancer plans. Both measures of radon potential were significantly associated with NCCCP cancer plans including radon activity. CONCLUSIONS: Geospatial analyses help to prioritize radon-related lung cancer activities. In areas with high potential for radon exposure, increasing knowledge about potential for radon exposure may result in increased radon testing, mitigation, or other radon reducing strategies, and ultimately reduction of lung cancer deaths.

Radon Testing Status in Schools by Radon Zone and School Location and Demographic Characteristics: United States, 2014.

Radon is a naturally occurring, radioactive, colorless, odorless gas, and the second leading cause of lung cancer. The 1990-1991 National School Radon Survey estimated that more than 70,000 schoolrooms nationwide had "high short-term radon levels." Using data from a nationally representative survey of schools in the United States (N = 568; response rate = 69%), we examined the location and demographic characteristics of U.S. schools that had ever been tested for radon and whether having been tested varied by radon zone, which predicts average indoor radon levels in U.S. counties. Overall, 46.0% (95% confidence interval [39.8%, 52.4%]) of schools reported that they had ever been tested for radon. Testing significantly varied by region, percentage of minority students, and radon zone. These findings highlight the need for improved awareness of radon testing in schools, as testing is the only way to identify when remediation is needed.

The use of gamma-survey measurements to better understand radon potential in urban areas.

Accounting for as much as 14% of all lung cancers worldwide, cumulative radon progeny exposure is the leading cause of lung cancer among never-smokers both internationally and in the United States. To understand the risk of radon progeny exposure, studies have mapped radon potential using aircraft-based measurements of gamma emissions. However, these efforts are hampered in urban areas where the built environment obstructs aerial data collection. To address part of this limitation, this study aimed to evaluate the effectiveness of using in situ gamma readings (taken with a scintillation probe attached to a ratemeter) to assess radon potential in an urban environment: DeKalb County, part of the Atlanta metropolitan area, Georgia, USA. After taking gamma measurements at 402 survey sites, empirical Bayesian kriging was used to create a continuous surface of predicted gamma readings for the county. We paired these predicted gamma readings with indoor radon concentration data from 1351 residential locations. Statistical tests showed the interpolated gamma values were significantly but weakly positively related with indoor radon concentrations, though this relationship is decreasingly informative at finer geographic scales. Geology, gamma readings, and indoor radon were interrelated, with granitic gneiss generally having the highest gamma readings and highest radon concentrations and ultramafic rock having the lowest of each. Our findings indicate the highest geogenic radon potential may exists in the relatively undeveloped southeastern part of the county. It is possible that in situ gamma, in concert with other variables, could offer an alternative to aerial radioactivity measurements when determining radon potential, though future work will be needed to address this project's limitations.