Resrad Parameter Sensitivity Simulation to Ascertain Local Parameters for Safety Assesment on Bangka Island Andry Setiawan(a), Mersi Kurniati(a), Dadong Iskandar(b), Hendra Adhi Pratama(b), Yuli Purwanto(b), Zico Pratama Putra(c)
a. Physics Departement, Faculty of Mathematics and Natural Science, IPB University
b. Research Center for Nuclear Material and Radioactive Waste Technology, National Research and Inovation Agency (BRIN)
c. Faculty of Information Technology, Nusa Mandiri University, Depok
Abstract
Tin slag and waste generated by tin processing often contain Technologically Enhanced Naturally Occurring Radioactive Materials (TENORM), which pose significant radiation risks to workers, the public, and the environment. To mitigate these risks, the development of a dedicated landfill facility is crucial for managing the radiological impact. This study analyzes the implications of storing TENORM waste, both prior to and following the construction of a landfill. The challenge of TENORM management persists, primarily due to the presence of long-lived radionuclides such as uranium-238 (U-238), thorium-232 (Th-232), and potassium-40 (K-40), which are often inadequately handled by industry. To address this, a landfill design was proposed and evaluated using RESRAD-Offsite 4.0 software, focusing on radiation safety and long-term exposure risks. To optimize safety and resource allocation, the study also investigated the sensitivity of RESRAD input parameters in estimating radiation dose and cancer risk. A total of 194 parameters were simulated, with approximately half exerting a significant influence on dose estimations. For example, the U-238 animal product intake transfer factor showed negligible sensitivity, affecting dose estimates by just 0.00001 mSv/year over 1,000 years. Conversely, precipitation demonstrated moderate sensitivity due to its effect on radionuclide leaching. Most notably, the fraction of time spent indoors on contaminated ground exhibited extremely high sensitivity, with dose estimates increasing by more than 11,000%. These findings underscore the importance of precise parameter selection in risk modeling and support the development of safer, more effective TENORM waste disposal strategies.
