4.5 Article

Assessing WHAM/Model VII against field measurements of free metal ion concentrations: model performance and the role of uncertainty in parameters and inputs

期刊

ENVIRONMENTAL CHEMISTRY
卷 8, 期 5, 页码 501-516

出版社

CSIRO PUBLISHING
DOI: 10.1071/EN11049

关键词

-

资金

  1. International Copper Association (ICA)
  2. International Council on Mining and Minerals (ICMM)
  3. International Lead Zinc Research Organization (ILZRO)
  4. Nickel Producers Environmental Research Association (NiPERA)
  5. Cobalt Development Institute (CDI)
  6. Rio Tinto Minerals
  7. International Chromium Development Association (ICDA)
  8. International Molybdenum Association (IMOA)
  9. European Aluminium Association (EAA)
  10. UK Natural Environment Research Council (NERC)
  11. Natural Environment Research Council [ceh010023] Funding Source: researchfish

向作者/读者索取更多资源

A key question in the evaluation of chemical speciation models is: how well do model predictions compare against speciation measurements? To address this issue, the performance of WHAM/Model VII in predicting free metal ion concentrations in field samples has been evaluated. A statistical sampling method considering uncertainties in input measurements, model parameters and the binding activity of dissolved organic matter was used to generate distributions of predicted free ion concentrations. Model performance varied with the metal considered and the analytical technique used to measure the free ion. Generally, the best agreement between observation and prediction was seen for aluminium, cobalt, nickel, zinc and cadmium. Important differences in agreement between model and observations were seen, depending upon the analytical technique. In particular, concentrations of free ion determined with voltammetric techniques were largely over-predicted by the model. Uncertainties in model predictions varied among metals. Only for aluminium could discrepancies between observation and model could be explained by uncertainties in input measurements and model parameters. For the other metals, the ranges of model predictions were mostly too small to explain the discrepancies between model and observation. Incorporating the effects of uncertainty into speciation model predictions allows for more rigorous assessment of model performance.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据