Integrating Empirically Dissolved Organic Matter Quality for WHAM VI using the DOM Optical Properties: A Case Study of Cu鈥揂l鈥揇OM Interactions
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  • 作者:Anthony Chappaz ; P. Jeff Curtis
  • 刊名:Environmental Science & Technology (ES&T)
  • 出版年:2013
  • 出版时间:February 19, 2013
  • 年:2013
  • 卷:47
  • 期:4
  • 页码:2001-2007
  • 全文大小:364K
  • 年卷期:v.47,no.4(February 19, 2013)
  • ISSN:1520-5851
文摘
Metal speciation is important for understanding the toxicity of metals in aquatic systems, and can be predicted for mixtures of metals in presence of dissolved organic matter (DOM) with thermodynamic models such as WHAM VI. The influence of the DOM source (quality) has been demonstrated, but is presently neglected in predicting Cu activity (WHAM VI). Here we determined the effect of aluminum (Al) competition on copper (Cu) complexation for four different DOMs, from a high-colored DOM (more humic) to a low-colored DOM (less humic). In presence of Al, free Cu activities (defined as free ion activity) increased, consistent with competition between Cu and Al for the same binding sites on all DOM. The apparent competition decreased with increasing DOM color. Equilibrium modeling of Cu speciation with WHAM VI explained 49% of the variance in measured Cu activity. When modified to integrate DOM quality using a new empirical coefficient F related to DOM optical properties, Cu activities predicted from WHAM VI were significantly improved to about 80% of the observed variance explained. The effects of Al on Cu activity were well predicted by WHAM VI. Subsequently, we compared the relative effects of DOM concentration, DOM quality, and Al competition with other determinants of Cu activity represented in legislation and scientific literature (pH and hardness), and qualitatively ranked them by their influence on Cu activity for normal ranges encountered in fresh waters using WHAM VI. Our experimental results indicate that DOM quality is an important variable that should be included in predictive models of ion speciation (WHAM VI) and eco-toxicological models such as the biotic ligand model (BLM).

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