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Critical evaluation of soil contamination assessment methods for trace metals

机译:痕量金属土壤污染评估方法的关键评估

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Correctly distinguishing between natural and anthropogenic trace metal contents in soils is crucial for assessing soil contamination. A series of assessment methods is critically outlined. All methods rely on assumptions of reference values for natural content. According to the adopted reference values, which are based on various statistical and geochemical procedures, there is a considerable range and discrepancy in the assessed soil contamination results as shown by the five methods applied to three weakly contaminated sites. This is a serious indication of their high methodological specificity and bias. No method with off-site reference values could identify any soil contamination in the investigated trace metals (Pb, Cu, Zn, Cd, Ni), while the specific and sensitive on-site reference methods did so for some sites. Soil profile balances are considered to produce the most plausible site-specific results, provided the numerous assumptions are realistic and the required data reliable. This highlights the dilemma between model and data uncertainty. Data uncertainty, however, is a neglected issue in soil contamination assessment so far. And the model uncertainty depends much on the site-specific realistic assumptions of pristine natural trace metal contents. Hence, the appropriate assessment of soil contamination is a subtle optimization exercise of model versus data uncertainty and specification versus generalization. There is no general and accurate reference method and soil contamination assessment is still rather fuzzy, with negative implications for the reliability of subsequent risk assessments.
机译:正确区分土壤中自然和人为的痕量金属含量对于评估土壤污染至关重要。严格概述了一系列评估方法。所有方法都依赖于自然含量参考值的假设。根据所采用的参考值(基于各种统计和地球化学程序),评估的土壤污染结果存在很大的范围和差异,如对三个弱污染场所的五种方法所显示的那样。这严重表明了它们的高方法学特异性和偏见。没有异地参考值的方法无法识别所调查的痕量金属(铅,铜,锌,镉,镍)中的任何土壤污染,而特定且灵敏的异地参考方法可用于某些地点。假设众多假设是现实的并且所需数据可靠,则土壤剖面平衡被认为可产生最合理的特定地点结果。这凸显了模型和数据不确定性之间的困境。到目前为止,数据不确定性是土壤污染评估中被忽略的问题。模型不确定性在很大程度上取决于原始天然痕量金属含量的特定地点的现实假设。因此,对土壤污染的适当评估是模型相对于数据不确定性以及规范相对于一般化的微妙优化。没有通用且准确的参考方法,土壤污染评估仍然相当模糊,对后续风险评估的可靠性产生负面影响。

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