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利用先进的表面络合模型模拟森林下的土壤化学:德国绍林根森林。

Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany.

机构信息

Alterra-Wageningen UR, Soil Science Centre, PO Box 47, 6700 AA Wageningen, The Netherlands.

出版信息

Environ Pollut. 2011 Oct;159(10):2831-9. doi: 10.1016/j.envpol.2011.05.002. Epub 2011 May 26.

Abstract

Various dynamic soil chemistry models have been developed to gain insight into impacts of atmospheric deposition of sulphur, nitrogen and other elements on soil and soil solution chemistry. Sorption parameters for anions and cations are generally calibrated for each site, which hampers extrapolation in space and time. On the other hand, recently developed surface complexation models (SCMs) have been successful in predicting ion sorption for static systems using generic parameter sets. This study reports the inclusion of an assemblage of these SCMs in the dynamic soil chemistry model SMARTml and applies this model to a spruce forest site in Solling Germany. Parameters for SCMs were taken from generic datasets and not calibrated. Nevertheless, modelling results for major elements matched observations well. Further, trace metals were included in the model, also using the existing framework of SCMs. The model predicted sorption for most trace elements well.

摘要

已经开发了各种动态土壤化学模型,以深入了解大气中硫、氮和其他元素对土壤和土壤溶液化学的影响。阴离子和阳离子的吸附参数通常针对每个站点进行校准,这阻碍了空间和时间上的推断。另一方面,最近开发的表面络合模型 (SCM) 已成功地使用通用参数集预测静态系统中的离子吸附。本研究报告了将这些 SCM 集合纳入动态土壤化学模型 SMARTml 中,并将该模型应用于德国 Solling 的一片云杉林。SCM 的参数取自通用数据集,未经校准。然而,主要元素的建模结果与观测结果非常吻合。此外,还使用现有的 SCM 框架将痕量金属纳入模型中。该模型很好地预测了大多数痕量元素的吸附。

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