Undeclared nuclear activities are challenging given the lack of information from the sites involved in such activities. Wide-area environmental sampling (WAES) can be an effective method to detect undeclared nuclear activities. However, it is crucial to address the potential risks during the WAES, including sample tampering or extortions. Therefore, tracking and monitoring of various on-site data is imperative to accurately interpret the status of samples and workers throughout the WAES process. ‘Environmental and Geographical Data Transfer (EGDT)’ was developed for the real-time monitoring of integrated on-site data. EGDT module is equipped with various sensors and can be attached to a worker’s uniform or a sample storage box. This study demonstrated the technical effectiveness of EGDT by exploring three experimental methodologies for feasibility assessment. Compared to the Normal Operation case, the inference of the Sample Extortion case was predominantly based on changes in lux and dose rate. The inference of the Out-of-Work-Area case primarily relied on changes in dose rate and acceleration. Finally, the preliminary evaluation of the performance of the developed prototype was conducted, and a foundation was established for enhancing the application in the WAES process.

Earth’s average temperature has risen by 0.78°C over the past century, and is projected to rise another 1.1 to 6.4°C over the next hundred years based on recent announced RCP8.5 climate change scenario. Small changes in the average temperature of the planet can translate to large and potentially dangerous shifts in biosphere. Based on climate change scenario, local distribution of well-known species should be changed in near future. Models, if applied appropriately, give useful and rapid predictions of the potential distribution of the target species. CLIMEX is one of modeling systems that may provide insights into the climatic factors that limit the geographical distribution of a species in different parts. Climatic parameters and the climate matching function of CLIMEX enable the risks of an exotic species as well as well-known species to be assessed by directly comparing the climatic condition of a given location with any number of other locations without knowing the full distribution of a species. However, CLIMEX supports only three locations in Korea (Seoul, Pusan and Kangnung province). We generated detail weather database of Korea for CLIMEX, and simulated using the data of American serpentine leafminer, Liriomyza trifolii (Burgess), a key pest and well-known species in Korea for application of future risk assessment under possible climate change condition in Korea.