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首页> 外文期刊>Geoderma: An International Journal of Soil Science >Probabilistic quality standards for heavy metals in soil derived from quality standards in crops.
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Probabilistic quality standards for heavy metals in soil derived from quality standards in crops.

机译:从作物质量标准中得出的土壤中重金属的概率质量标准。

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摘要

This paper contributes to the development of critical levels of heavy metals in soil at which functions of the soil are safeguarded. For agriculture production, one of the key aspects is food safety. In this study, a quality standard for Cd in soil is derived from the EC-food quality standard for Cd in wheat. The transfer of the Cd in the soil to the crop is modelled by a regression model. Such models offer the possibility of calculating probabilistic soil quality standards from food quality standards. Given the food quality standard and a maximum acceptable probability of exceeding this standard, the Cd concentrations in soil at which the probability of excess Cd in wheat equals this maximum is calculated by the inverse use of the regression model. It is important to account for errors in the Cd measurements in wheat used to calibrate the model. Neglecting these errors gives conservative estimates of the p% critical threshold for p smaller than 50. For representative arable soils, the 5% critical threshold varies from 0.5 mg kg-1 (non-calcareous sand soils) to 3 mg kg-1 (calcareous clay soils). Even at low probability levels, the model must be extrapolated for many arable soils, and therefore, more calibration data must be collected, especially from sand soils with relatively low pH values. Validation of the model with data from contaminated bed sediments in the floodplain of the Meuse showed that the model seriously overestimated the critical threshold, which can be explained by the higher availability of Cd in contaminated soils..
机译:本文有助于保护土壤功能的临界重金属水平的发展。对于农业生产而言,关键方面之一是食品安全。在这项研究中,土壤中Cd的质量标准源自EC小麦中Cd的食品质量标准。土壤中Cd向作物的转移通过回归模型进行建模。这种模型提供了根据食品质量标准计算概率性土壤质量标准的可能性。给定食品质量标准和超过该标准的最大可接受概率,则通过反向使用回归模型来计算土壤中的Cd浓度(小麦中Cd过量的概率等于该最大值)。重要的是要考虑用于校准模型的小麦中Cd测量值的误差。忽略这些误差,可以得出p小于50的p%临界阈值的保守估计。对于代表性的耕作土壤,5%临界阈值从0.5 mg kg-1(非钙质砂土)到3 mg kg-1(钙质)不等。黏土)。即使在低概率水平下,也必须对许多耕作土壤外推模型,因此,必须收集更多的校准数据,尤其是从pH值相对较低的沙土中。用Meuse洪泛区受污染床沉积物的数据对模型进行验证,结果表明该模型严重高估了临界阈值,这可以用受污染土壤中Cd的较高利用率来解释。

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