Statistical approach to assess radon-222 long-range atmospheric transport modelling and its associated gamma dose rate peaks
نویسندگان
چکیده
Abstract. There is a need for validation framework long-range atmospheric transport modelling dedicated to radionuclides. For distances greater than 50 km, the of radionuclide deposition and ambient gamma dose rate evaluation are particularly difficult validate, since it has been mainly only observed after accidents Chernobyl Fukushima. however natural wet phenomenon leading numerous well-observed events: scavenging radon-222 progeny by rain. Radon-222 exhalation from soil atmosphere, its decay, progeny, own transport, their deposition, consequent then modelled at European scale. This whole radon model (exhalation) (deposition) needs be validated comparison with observations. The biggest benefit this case study number events that serve as comparison. statistical performance model, we compared results observations over period two years, gathering more 15 000 peaks 10 nSv h−1 above background radiation. Two sets metrics were used assess agreement between observations: on basis (peak peak) continuously (whole time series rates air concentrations). Particular attention was paid defining in order remove radiation level exclude outlier stations. We found 48 % well modelled, fraction which can rise up 89 being tolerant success criteria. proven correct magnitude, room substantial improvement. Overall, shows better recall precision: i.e. tendency produce false positives negatives. It also less effective reproducing highest peaks. Exhalation, vertical mixing have identified three main features could improve model. Now validated, all limitations, may primary purpose, input data. test any national or continental Moreover, useful learn how properly use data an network, compare Finally, some interesting concerning assessment outdoor concentrations became apparent.
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ژورنال
عنوان ژورنال: Advances in Geosciences
سال: 2022
ISSN: ['1680-7359', '1680-7340']
DOI: https://doi.org/10.5194/adgeo-57-109-2022