Characterizing Dissolved Organic Matter Using PARAFAC Modeling of Fluorescence Spectroscopy: A Comparison of Two Models
Characterizing Dissolved Organic Matter Using PARAFAC Modeling of Fluorescence Spectroscopy: A Comparison of Two Models
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DOI：
10.1021/es900143g
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发表时间：
2009-08-15
影响因子：
11.4
通讯作者：
White, Dan
中科院分区：
文献类型：
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作者：
Fellman, Jason B.;Miller, Mathew P.;White, Dan
我们评估了将荧光激发-发射矩阵（EEMs）拟合到先前验证的PARAFAC模型是否是建立原始模型的可接受替代方案。要做到这一点，我们建立了一个10个组件的模型，使用307个从阿拉斯加东南部的土壤和溪流收集的EEM。然后将所有307个EEM拟合到Cory和McKnight（Environ. Sci. Technol，2005，39，8142-8149）。用于评估EEM是否很好地拟合CM模型的第一种方法是对剩余EEM的评估，并且我们发现22个EEM被CM模型拟合得很差。我们验证EEM是否很好地拟合CM模型的第二个措施是比较PARAFAC分量和DOM测量值的百分比贡献之间的相关性（例如，溶解性营养盐浓度），两种模型间差异不显著（p > 0.05）。这些结果支持当DOM从相似的环境中收集时，将EEM拟合到现有模型的方法，这可以潜在地减少构建原始PARAFAC模型时的一些问题。然而，重要的是要认识到，一些敏感性或生态解释能力可能会丢失时，适合环境要素模型的现有模式。
We evaluated whether fitting fluorescence excitation-emission matrices (EEMs) to a previously validated PARAFAC model is an acceptable alternative to building an original model. To do this, we built a 10-component model using 307 EEMs collected from southeast Alaskan soil and streamwater. All 307 EEMs were then fit to the existing model (CM) presented in Cory and McKnight (Environ. Sci. Technol, 2005, 39, 8142-8149), The first approach for evaluating whether the EEMs were fit well to the CM model was an evaluation of the residual EEMs, and we found 22 EEMs were fit poorly by the CM model. Our second measure for verifying whether EEMs were fit well to the CM model was a comparison of correlations between the percent contribution of PARAFAC components and DOM measurements (e.g., dissolved nutrient concentrations), and we found no significant difference (p > 0.05) between the two models. These results support the approach of fitting EEMs to an existing model when DOM is collected from similar environments, which can potentially reduce some of the problems when building an original PARAFAC model. However, it is important to recognize that some of the sensitivity or ecological interpretative power may be lost when fitting EEMs to an existing model.