Factors controlling dissolved 137Cs concentrations in east Japanese Rivers
Factors controlling dissolved 137Cs concentrations in east Japanese Rivers
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日本东部河流溶解 137Cs 浓度的控制因素
DOI：
10.1016/j.scitotenv.2019.134093
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发表时间：
2019
影响因子：
9.8
通讯作者：
Hayashi Seiji
中科院分区：
文献类型：
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作者：
Tsuji Hideki;Ishii Yumiko;Shin Moono;Taniguchi Keisuke;Arai Hirotsugu;Kurihara Momo;Yasutaka Tetsuo;Kuramoto Takayuki;Nakanishi Takahiro;Lee Sangyoon;Shinano Takuro;Onda Yuichi;Hayashi Seiji
为探讨影响福岛核电站事故地区河水中溶解放射性铯浓度的主要因素，对流域内66个站点的137 Cs溶解浓度与土地利用、土壤成分、地形和水质因子的相关性进行了评估。结果表明，地形湿润指数与137Cs标准化浓度呈显著正相关。在欧洲河流中也发现了类似的正相关性，因为湿地地区的沼泽有机土壤中137Cs的保留较弱，主要分布在平原上。然而，对于小日本河流流域，在流域的建筑面积比强烈影响dissolved137Cs浓度。其中一个原因可能是因为高浓度的溶质，如K+和溶解的有机碳，在城市地区排放会阻碍137Cs吸收到土壤颗粒。以地形、土地利用、土壤成分和水质数据为解释变量，构建了一个多元回归方程来预测归一化的137Cs溶解浓度。最好的模型有建设用地作为主要的预测。当比较两个多元回归模型，其中的解释变量仅限于（1）土地利用和土壤成分和（2）水质，水质模型低估了高归一化dissolve137Cs浓度在城市地区。这表明，由于水质的影响，城市地区溶解态137Cs浓度值不能完全用137Cs的固液分布来解释，而城市地区某些特定的137Cs源会控制溶解态137Cs浓度。
To investigate the main factors that control the dissolved radiocesium concentration in river water in the area affected by the Fukushima Daiichi nuclear power plant accident, the correlations between the dissolved137Cs concentrations at 66 sites normalized to the average137Cs inventories for the watersheds with the land use, soil components, topography, and water quality factors were assessed. We found that the topographic wetness index is significantly and positively correlated with the normalized dissolved137Cs concentration. Similar positive correlations have been found for European rivers because wetland areas with boggy organic soils that weakly retain137Cs are mainly found on plains. However, for small Japanese river watersheds, the building area ratio in the watershed strongly affected the dissolved137Cs concentration. One reason for this would be because the high concentrations of solutes, such as K+and dissolved organic carbon, discharged in urban areas would inhibit137Cs absorption to soil particles. A multiple regression equation was constructed to predict the normalized dissolved137Cs concentration with the topography, land use, soil component, and water quality data as explanatory variables. The best model had the building land use as the primary predictor. When comparing two multiple regression models in which the explanatory variables were limited to (1) the land use and soil composition and (2) the water quality, the water quality model underestimated the high normalized dissolve137Cs concentration in urban areas. This poor reproducibility indicates that the dissolved137Cs concentration value in urban areas cannot be solely explained by the solid-liquid distribution of137Cs owing to the influence of the water quality, but some specific137Cs sources in urban areas would control the dissolved137Cs concentration.