Article ID Journal Published Year Pages File Type
6329806 Science of The Total Environment 2014 7 Pages PDF
Abstract

•A double exponential model was used to model leachable cesium loss from canopies.•The model could not reproduce variation observed.•Rainfall was identified as the dominant factor controlling the variation.•A rainfall parameter was used to develop an improved double exponential model.•The improved model gives a better estimation of leaf cesium leaching.

The Fukushima accident dispersed significant amounts of radioactive cesium (Cs) in the landscape. Our research investigated, from June 2011 to November 2013, the mobility of leachable Cs in forests canopies. In particular, 137Cs and 134Cs activity concentrations were measured in rainfall, throughfall, and stemflow in broad-leaf and cedar forests in an area located 40 km from the power plant.Leachable 137Cs loss was modeled by a double exponential (DE) model. This model could not reproduce the variation in activity concentration observed. In order to refine the DE model, the main physical measurable parameters (rainfall intensity, wind velocity, and snowfall occurrence) were assessed, and rainfall was identified as the dominant factor controlling observed variation. A corrective factor was then developed to incorporate rainfall intensity in an improved DE model.With the original DE model, we estimated total 137Cs loss by leaching from canopies to be 72 ± 4%, 67 ± 4%, and 48 ± 2% of the total plume deposition under mature cedar, young cedar, and broad-leaf forests, respectively. In contrast, with the improved DE model, the total 137Cs loss by leaching was estimated to be 34 ± 2%, 34 ± 2%, and 16 ± 1% of the total plume deposition under mature cedar, young cedar, and broad-leaf forests, respectively. The improved DE model corresponds better to observed data in literature.Understanding 137Cs and 134Cs forest dynamics is important for forecasting future contamination of forest soils around the FDNPP. It also provides a basis for understanding forest transfers in future potential nuclear disasters.

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Life Sciences Environmental Science Environmental Chemistry
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