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In this section, you can access to the latest technical information related to the FUTURE project topic.
Development and calibration of a modifiable passive sampler for monitoring atmospheric tritiated water vapor in different environments
Anthropogenic release of tritium from nuclear facilities is expected to increase significantly in the coming decades, which may cause radiation exposure to humans through the contamination of water and food chains. It is necessary and urgent to acquire detailed information about tritium in various environments for studying its behavior and assessing the potential radiation risk. In the atmosphere, although the passive sampling technique provides a low-cost and convenient way to characterize the dynamics of tritiated water vapor (HTO), a single, simple sampler configuration makes it difficult to collect sufficient and representative samples within the expected period from different environments. In this study, we systematically studied the impacts of sampler configurations on sampling performance and proposed a modifiable sampler design by scaling sampler geometry and adjusting absorbent to achieve different monitoring demands. The samplers were subsequently deployed at five sites in China and Germany for the field calibration and the measured results exhibited a good agreement between the adsorption process obtained in sites corrected with diffusion coefficient and the one calibrated in Shanghai. This suggests the feasibility of predicting sampling performance in the field based on known data. Finally, we developed a strategy for sampler modification and selection in different environments and demonstrated that using easily obtainable environmental data, our sampler can be optimized for any area without any time-consuming preliminary experiments. This work provides a scientific basis for establishing high-resolution atmospheric HTO database and expands the conventional empirical sampler design paradigm by demonstrating the feasibility of using quantitative indices for sampler performance customization.
» Author: Bin Feng, Georg Steinhauser, Weihai Zhuo, Zhiling Li, Yupeng Yao, Tobias Blenke, Chao Zhao, Franz Renz, Bo Chen
» Publication Date: 01/11/2022
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