Ridge regression modeling of background gamma radiation and radiological risk assessment at NAK steel limited dumpsite, Katsina, Nigeria

Rapid urbanization and industrial activities in Nigeria have raised concerns about gamma radiation exposure, emphasizing the need for accurate monitoring to protect public health. This study addresses the limited application of advanced statistical techniques for radiological risk assessment in Nigerian industrial dumpsites, assessing both distribution patterns and potential health risks through statistical analysis and modeling. Measurements of naturally occurring radionuclides (²³⁸U, ²³²Th, and ⁴⁰K) were conducted using a NaI(Tl) gamma ray detector. Analysis revealed gamma dose rates ranging from 24.85 to 222.31 nGy/h, with an average of 47.55 nGy/h, below the global average of 57 nGy/h. Though most measurements (average: 47.55 nGy/h) were below the global average (57 nGy/h), localized hotspots (e.g., 222.31 nGy/h) were identified. Key radiological parameters, including the gamma index, radium equivalent, and hazard indices, were within internationally accepted safety limits. Similarly, the estimated annual effective dose remained below the 1 mSv/year threshold for public exposure. A ridge regression model was developed to address multicollinearity among predictors and serve as a predictive model for estimating background radiation levels based on radiological factors such as the gamma index and radium equivalent. The annual effective dose ranged from 0.030 to 0.273 mSv/y, with a mean of 0.058 mSv/y, and the excess lifetime cancer risk was between 0.107 and 0.954 × 10⁻⁶, averaging 0.204 × 10⁻⁶, suggesting that health risks are minimal overall, though some localized anomalies do need to be monitored. The model achieved a high prediction accuracy of 98 %, effectively identifying anomalous areas and demonstrating strong agreement with measured gamma dose rates. Additionally, assessments of the annual gonadal dose equivalent and excess lifetime cancer risk (ELCR) indicated low radiation-related health risks across the site. These findings provide a baseline for industrial dumpsite radioactivity and establish a framework for ongoing radiological monitoring and risk assessment.