Technical note: Effects of iron(II) on fluorescence properties of dissolved organic matter at circumneutral pH

Modern fluorescence spectroscopy methods, including excitation–emission matrix (EEM) spectra parsed using parallel factor analysis (PARAFAC) statistical approaches, are widely used to characterize dissolved organic matter (DOM) pools. The effect of soluble reduced iron, Fe(II), on EEM spectra can be significant but is difficult to quantitatively assign. In this study, we examine the effects of Fe(II) on the EEM spectra of groundwater samples from an anaerobic deltaic aquifer containing up to 300 mg L−1 Fe(II), located a few kilometres from the ocean and adjacent to the Fraser River in Richmond, British Columbia, Canada. We added varying quantities of Fe(II) into groundwater samples to evaluate Fe(II)–DOM interactions. Both the overall fluorescence intensity and the intensity of the primary peak, a humic-like substance at excitation and emission wavelengths of 239 and 441–450 nm (peak A), respectively, decreased by approximately 60 % as Fe(II) concentration increased from 1 to 306 mg L−1. Furthermore, the quenching effect was nonlinear and proportionally stronger at Fe(II) concentrations below 100 mg L−1. This nonlinear relationship suggests a static quenching mechanism. In addition, DOM fluorescence indices are substantially influenced by the Fe(II) concentration. With increasing Fe(II), the fluorescence index (FI) shifts to higher values, the humidification index (HIX) shifts to lower values, and the freshness index (FrI) shifts to higher values. Nevertheless, the 13-component PARAFAC model showed that the component distribution was relatively insensitive to Fe(II) concentration; thus, PARAFAC may be a reliable method for obtaining information about the DOM composition and its redox status in Fe(II)-rich waters. By characterizing the impacts of up to 300 mg L−1 Fe(II) on EEMs using groundwater from an aquifer which contains similar Fe(II) concentrations, we advance previous work which characterized impacts of lower Fe(II) concentrations (less than 2 mg L−1) on EEMs.

Random effect models for multivariate mixed data: A Parafac-based finite mixture approach

We discuss a flexible regression model for multivariate mixed responses. Dependence between outcomes is introduced via the joint distribution of discrete outcome- and individual-specific random effects that represent potential unobserved heterogeneity in each outcome profile. A different number of locations can be used for each margin, and the association structure is described by a tensor that can be further simplified by using the Parafac model. A case study illustrates the proposal.

Spectral characterization of the effect of gas-water ratio on dissolved organic nitrogen variation along biological aerated filter for micropolluted source water pre-treatment

In order to improve our understanding of dissolved organic nitrogen (DON) variation characteristics in the biological aerated filter (BAF) for drinking water treatment, this study focused on gas-water ratio, a controlling factor of BAF operation, to study spectral characteristics of DON under different gas-water ratio conditions (0, 0.5:1, 2:1 and 10:1). The variations of dissolved organic carbon (DOC) and DON concentrations showed that DOC removal efficiency was consistent with DON concentration, both of which increased with the increase of gas-water ratio, but the increase gradually reduced and was certain limited. Three-dimensional excitation–emission matrix (3D-EEM) spectroscopy combined with parallel factor (PARAFAC) model and fluorescence regional integration (FRI) technique were applied to analyze the effect of gas-water ratio on spectral characteristics of DON, PARAFAC analysis results identified the main component of DON were tryptophan and protein related substances. The resistances of various fluorescent substances in the FRI technique under the influence of gas-water ratio were shown as: protein substances > humic acid and fulvic acid substances ≈ SMPs-like substances. Correlation analysis showed that the variation of FIS from PARAFAC model was consistent with corresponding normalized integration volume in FRI analysis under different gas-water ratios.

A New Application of PARAFAC Model to UPLC Dataset for the Quantitative Resolution of a Tri-Component Drug Mixture

In the presented work, a three-way analysis of ultra-performance liquid chromatography-photodiode array (UPLC-PDA) dataset was performed by parallel factor analysis (PARAFAC) for quantitatively resolving a ternary mixture containing paracetamol and methocarbamol with indapamide selected as an internal standard in their co-eluted chromatographic conditions. Paracetamol and methocarbamol were quantified in the working range between 3–24 and 5–50 μg/mL by applying PARAFAC decomposition to UPLC-PDA data array obtained under unresolved chromatographic peak conditions. To compare the experimental results provided by co-eluted UPLC-PARAFAC method, an ordinary UPLC method was developed ensuring proper separation of the peaks. The performance of both PARAFAC and ordinary UPLC methods were assessed by quantifying independent test samples, intra- and inter-day samples and spiked samples of pharmaceutical preparations. Then, both methods were applied for quantitative estimation of the related drugs in a commercial pharmaceutical preparation. In this study, PARAFAC method was proved to be a very powerful alternative for the quality control of pharmaceutical preparations containing paracetamol and methocarbamol even in their co-eluted chromatograms with high precision and accuracy in a short chromatographic runtime of 1.2 min.

Factor Uniqueness of the Structural Parafac Model

Factor analysis is a well-known method for describing the covariance structure among a set of manifest variables through a limited number of unobserved factors. When the observed variables are collected at various occasions on the same statistical units, the data have a three-way structure and standard factor analysis may fail. To overcome these limitations, three-way models, such as the Parafac model, can be adopted. It is often seen as an extension of principal component analysis able to discover unique latent components. The structural version, i.e., as a reparameterization of the covariance matrix, has been also formulated but rarely investigated. In this article, such a formulation is studied by discussing under what conditions factor uniqueness is preserved. It is shown that, under mild conditions, such a property holds even if the specific factors are assumed to be within-variable, or within-occasion, correlated and the model is modified to become scale invariant.

Technical note: Effects of iron(II) on fluorescence properties of dissolved organic matter at circumneutral pH

Modern fluorescence spectroscopy methods, including excitation-emission matrix (EEMs) spectra parsed using parallel factor analysis (PARAFAC) statistical approaches, are widely used to characterize dissolved organic matter (DOM) pools. The effect of soluble reduced iron, Fe(II), on EEM spectra can be significant, but is difficult to quantitatively assign. In this study, we examine the effects of Fe(II) on the EEM spectra of groundwater samples from an anaerobic deltaic aquifer containing up to 300 mg/L Fe(II), located a few kilometers from the ocean, adjacent to the Fraser River in Richmond, British Columbia, Canada. We added varying quantities of Fe(II) into groundwater samples to evaluate Fe(II)-DOM interactions. Both the overall fluorescence intensity and the intensity of the primary peak, a humic-like substance at excitation/emission wavelengths 239/441–450 nm (Peak A), decreased by approximately 60 % as Fe(II) concentration increased from 1 to 306 mg/L. Furthermore, the quenching effect was non-linear and proportionally stronger at Fe(II) concentrations below 100 mg/L. This non-linear relationship suggests a static quenching mechanism. In addition, DOM fluorescence indices are substantially influenced by the Fe(II) concentration. With increasing Fe(II), the fluorescence index (FI) tends to shift to a more microbial-derived origin, and both the humidification index (HIX) and freshness index (FrI) indicate more freshly produced DOM. Nevertheless, the 13-component PARAFAC model showed that the component distribution was relatively insensitive to Fe(II) concentration, and thus, PARAFAC may be a reliable method for obtaining information about the DOM composition and its redox status in Fe(II)-rich waters. By characterizing the impacts of up to 300 mg/L Fe(II) on EEMs using groundwater from an aquifer which contains similar Fe(II) concentrations, we advance previous works which characterized impacts of lower Fe(II) concentrations (less than 2 mg/L) on EEMs.

Dimensionality Reduction Based on PARAFAC Model

In hyperspectral image analysis, dimensionality reduction is a preprocessing step for hyperspectral image (HSI) classification. Principal component analysis (PCA) reduces the spectral dimension and does not utilize the spatial information of an HSI. To solve it, the tensor decompositions have been successfully applied to joint noise reduction in spatial and spectral dimensions of hyperspectral images, such as parallel factor analysis (PARAFAC). However, the PARAFAC method does not reduce the dimension in the spectral dimension. To improve it, two new methods were proposed in this article, that is, combine PCA and PARAFAC to reduce both the dimension in the spectral dimension and the noise in the spatial and spectral dimensions. The experimental results indicate that the new methods improve the classification compared with the PARAFAC method.

Dynamics of dissolved organic matter in a wastewater effluent-impacted Japanese urban stream: characteristics, occurrence and photoreactivity of fluorescent components

We report the results of using the excitation–emission matrix (EEM) method combined with parallel factor analysis (PARAFAC) to investigate the characteristics and occurrence of dissolved organic matter (DOM) in an urban stream impacted by effluent from a wastewater treatment plant (WWTP). The PARAFAC model divides the bulk EEM spectra into six individual fluorescent components with three humic-like components (C1–C3), two protein-like components (C4 and C5) and a wastewater-derived component (C6). In general, intensities of fluorescent components are abundant in WWTP effluent impacted samples, thus showing that such an effluent is a major source of DOM in urban rivers, but C5 is considered to have autochthonous sources within the stream. In areas where the effluent is released, the fluorescent intensity from components (except C5) gradually decreases as these components are transported downstream. However, concentrations of dissolved organic carbon remain almost constant downstream of the release area. These results would be attributed to degradation and/or modification of fluorophore. Photolysis experiments confirmed that fluorescent intensities can decrease with increase of irradiation times. C6 particularly showed a rapid photodegradation, remaining only 24.1% after 48 h photolysis. These findings would be important when assessing DOM source and water quality in aquatic environments by EEM-PARAFAC.