Seasonal variation and structural influences on indoor radon exposure in residential buildings of Khuzestan Province

Radon, a radioactive gas and the second leading cause of lung cancer, poses significant health risks in enclosed spaces. This study examines radon concentrations in residential buildings across Khuzestan Province, Iran, exploring seasonal variations and building-related influences, to establish a baseline radon profile and inform public health strategies. A cross-sectional study measured indoor radon levels in 343 homes using CR-39 solid-state nuclear track detectors during the cold (December-February) and warm (June-August) seasons of 2024. Stratified random sampling ensured representativeness across Khuzestan, varying in geology and urban density. Key variables included building age, height, floor type, and structural framework. Spatial distribution was mapped via Inverse Distance Weighting (IDW) and Ordinary Kriging (OK). Statistical analyses (t-tests, ANOVA) assessed differences (p < 0.05). Mean radon concentrations were higher in the cold season (119.93 ± 113.15 Bq/m²) than in the warm season (72.99 ± 41.16 Bq/m²), with northern cities like Dezful (279.05 Bq/m²) exceeding WHO (100 Bq/m²) and EPA (148 Bq/m²) thresholds. The estimated annual effective doses (AEDs) ranged from 0.78 to 7.04 mSv/year, with higher values during the cold season. Older concrete buildings (> 15 years) and ground-floor units showed significantly elevated levels (p < 0.001). Floor type influenced warm-season concentrations (p = 0.011), with mosaic floors highest (91.32 Bq/m²). Spatial analysis identified northern mountainous regions as radon hotspots, especially in the cold season. Seasonal and structural factors significantly affect radon levels in Khuzestan, highlighting public health risks in high-radon zones. Mitigation strategies, such as ventilation improvements in older concrete homes, are critical. This dataset fills a critical knowledge gap in Iran's national radon profile and provides an essential baseline for future geospatial health risk modeling, mitigation planning, and policy development.