Next-Generation Environmental Radiation Monitoring: Advances in Sensors, Data Analytics, and Earth System Integration

Abstract

The convergence of next-generation sensors, sophisticated data analytics, and Earth system models has fundamentally transformed the landscape of environmental radiation monitoring. These technological synergies have collectively enhanced the accuracy, spatial coverage, and real-time responsiveness of detection systems, enabling more precise identification and assessment of radiation exposure risks. This article systematically reviews recent progress in sensor technologies, including improved sensitivity and durability, alongside the growing role of machine learning algorithms in processing complex monitoring data and distinguishing anomalous radiation patterns from background noise. A central focus is the integration of radiation data into Earth system models, which facilitates the simulation of radionuclide dispersion and environmental fate, thereby supporting predictive capabilities and informed decision-making during radiological emergencies. Furthermore, the article highlights the practical benefits of real-time monitoring networks and early warning systems in strengthening disaster preparedness and safeguarding public health. Despite these notable advances, significant challenges remain, including issues related to sensor calibration, cross-platform data integration, infrastructure deployment, and cybersecurity. Looking ahead, continued research, technological innovation, and international collaboration are essential to enhance the reliability, scalability, and global interoperability of these systems. Ultimately, these developments not only contribute to reducing radiation-related risks but also align with broader sustainability objectives, particularly in supporting environmental health, climate resilience, and evidence-based policy formulation under the United Nations Sustainable Development Goals.