Simultaneous analysis of the photocatalytic degradation of polycyclic aromatic hydrocarbons using three-dimensional excitation–emission matrix fluorescence and parallel factor analysis

Fluorescent spectroscopy paired with parallel factor analysis for quantitative monitoring of phenanthrene biodegradation and metabolite formation

Polycyclic aromatic hydrocarbons (PAHs) are a class of environmental contaminants released into the environment from both natural and anthropogenic sources that are associated with carcinogenic, mutagenic, and teratogenic health effects. Many remediation strategies for the treatment of PAH contaminated material, including bioremediation, can lead to the formation of toxic transformation products. Analytical techniques for PAHs and PAH transformation products often require extensive sample preparation including solvent extraction and concentration, chromatographic separation, and mass spectrometry to identify and quantify compounds of interest. Excitation-emission matrix (EEM) fluorescent spectroscopy paired with parallel factor analysis (PARAFAC) is an approach for analyzing PAHs that eliminates the need for extensive sample preparation and separation techniques before analysis. However, this technique has rarely been applied to monitoring PAH biotransformation and formation of PAH metabolites. The objectives of this research were to compare an established targeted analytical method to two-dimensional fluorescent spectroscopy and combined EEM-PARAFAC methods to monitor phenanthrene degradation by a bacterial pure culture, Mycobacterium Strain ELW1, identify and quantify phenanthrene transformation products, and derive kinetic constants for phenanthrene degradation and metabolite formation. Both phenanthrene and its primary transformation product, trans-9,10-dihydroxy-9,10-dihydrophenanthrene, were identified and quantified with the EEM-PARAFAC method. The value of the EEM-PARAFAC method was demonstrated in the superiority of sensitivity and accuracy of quantification to two-dimensional fluorescent spectroscopy. Quantification of targets and derivation of kinetic constants using the EEM-PARAFAC method were validated with an established gas chromatography-mass spectrometry (GC-MS) method. To the authors' knowledge, this is the first study to use an EEM-PARAFAC method to monitor, identify, and quantify both PAH biodegradation and PAH metabolite formation by a bacterial pure culture.

Combined fluorescent measurements, parallel factor analysis and GC-mass spectrometry in evaluating the photodegradation of PAHS in freshwater systems

To better understand the transformation and photochemical fate of PAHs in aquatic environments, a custom-designed closed-circuit recirculation photodegradation system, combined with inline semi-continuous fluorescence and absorbance measurements, as well as modelling of excitation-emission (EEM) measurements with parallel factor analysis (PARAFAC), and GC-MS analysis, were combined to create a robust tool for holistically assessing the photodegradation of individual PAHs, their mixtures and photoproduct formation. Selected compounds included in the US EPA priority list, representing 2- to 6-ring compounds, were monitored individually and in mixtures, during 24 h photodegradation experiments. Experiments were conducted in solutions simulating ideal (ultrapure water) and environmentally relevant conditions (1.00 mg L^-1 Suwannee River Natural Organic Matter (SRNOM)). The fluorescence, primary PARAFAC components and quantification data obtained by GC-MS, indicated that the decline in parent molecule concentration occurred rapidly within 200 min. The degradation rates of parent PAHs increased with aromaticity (6-ring ≫ 2-ring PAHs) and followed pseudo-first order degradation kinetics. The presence and transformation of degradation products, were captured by PARAFAC. NOM influenced the diversity of photoproducts. From the GC-MS results, photoproducts were only detected in Ant, BAnt and the PAH mixture solutions, but optical property analyses indicated that diverse changes occurred with all PAHs. Spectrometric and chromatographic data demonstrated that parent PAHs and photoproducts co-existed at various stages, which is significant for freshwater systems contaminated with these compounds if photoproducts have higher-toxic potential. These results may be used to model the hazard-potential associated with PAHs present in freshwater systems and understanding the mechanisms that govern their environmental fate.

Electro-Fenton with peroxi-coagulation as a feasible pre-treatment for high-strength refractory coke plant wastewater: Parameters optimization, removal behavior and kinetics analysis

Electro-Fenton (EF) with peroxi-coagulation (PC) as an emerging electro-chemical advanced oxidation method has been extensively applied to treat refractory wastewater. However, the studies on the pretreatment of the raw coke plant wastewater by EF process were still lacking. In this study, a lab-scale EF system (Fe as anode and graphite as cathode) achieved the highest COD removal of 69.2% based on the preliminary experiments. The process parameters and corresponding COD removal performance were further optimized using response surface methodology (RSM) combined with Box-Behnken experimental design (BBD). The optimal conditions were obtained as: 3.2 mA cm^-2 of current density, 2 h of the reaction time and 2.6 of the initial pH value, with the COD removal reaching 70.0%. Fourier infrared (FTIR), fluorescence excitation-emmission matrix (EEM) and gas chromatography-mass spectrometry (GC-MS) also revealed the degradation behaviors of dissolved organic matters (DOMs) by characterizing their structures and compositions before and after EF pretreatment, thus greatly improving the biodegradability of the wastewater. Moreover, the EF process for COD removal well followed third-order kinetics model. These findings give helpful guidance to design, optimize and control the EF process as a favourable pretreatment for actual refractory coking wastewater in practice.

Classification of water contamination developed by 2-D Gabor wavelet analysis and support vector machine based on fluorescence spectroscopy

The identification of the specific categories of pollutants in the urban water supply system is necessary. Traditional detection methods are based mainly on common water quality indicators. However, inspecting these water quality indicators is made difficult by issues such as long analysis time, insufficient sensitivity, need for reagents, and generation of waste liquid. These problems hinder high-frequency water detection and monitoring. In this study, three-dimensional (3D) fluorescence spectroscopy is adopted as a monitoring method for water quality. An identification method based on two-dimensional (2D) Gabor wavelets and support vector machine (SVM) multi-classification is also proposed. The Delaunay triangulation method for interpolation is used to pre-process 3D fluorescence spectra and thereby eliminate Rayleigh scattering and Raman scattering. A 2D Gabor wavelet function generated by filters of different scales and rotation angles is proposed to extract the features of the spectra. The block statistics method, based on Gabor feature description, is employed to enhance the efficiency in describing spectra features. Then, multiple SVM classifiers are used in pollutant classification and recognition. By comparing the proposed method with principal component analysis, which is a commonly used feature extraction method, this study finds that the application of 2D Gabor wavelets and block statistics can effectively describe the characteristics of 3D fluorescence spectra. Moreover, 2D Gabor wavelets achieve high classification accuracy, especially for substances with closely positioned or overlapping characteristic peaks.

Oil species identification technique developed by Gabor wavelet analysis and support vector machine based on concentration-synchronous-matrix-fluorescence spectroscopy

Concentration-synchronous-matrix-fluorescence (CSMF) spectroscopy was applied to discriminate the oil species by characterizing the concentration dependent fluorescence properties of petroleum related samples. Seven days weathering experiment of 3 crude oil samples from the Bohai Sea platforms of China was carried out under controlled laboratory conditions and showed that weathering had no significant effect on the CSMF spectra. While different feature extraction methods, such as PCA, PLS and Gabor wavelet analysis, were applied to extract discriminative patterns from CSMF spectra, classifications were made via SVM to compare their respective performance of oil species recognition. Ideal correct rates of oil species recognition of 100% for the different types of oil spill samples and 92% for the closely-related source oil samples were achieved by combining Gabor wavelet with SVM, which indicated its advantages to be developed to a rapid, cost-effective, and accurate forensic oil spill identification technique.

Photochemical degradation of phenanthrene as a function of natural water variables modeling freshwater to marine environments

Photolysis rates of phenanthrene as a function of ionic strength (salinity), oxygen levels and humic acid concentrations were measured in aqueous solution over the range of conditions found in fresh to marine waters. Photolysis followed first order kinetics, with an estimated photodegradation half-life in sunlight in pure water of 10.3±0.7h, in the mid-range of published results. Photolysis rate constants decreased by a factor of 5 in solutions with humic acid concentrations from 0 to 10 mg C L(-1). This decrease could be modeled entirely based on competitive light absorption effects due to the added humics. No significant ionic strength or oxygen effects were observed, consistent with a direct photolysis mechanism. In the absence of significant solution medium effects, the photodegradation lifetime of phenanthrene will depend only on solar fluxes (i.e. temporal and seasonal changes in sunlight) and not vary with a freshwater to marine environment.

Dissolved organic matter with multi-peak fluorophores in landfill leachate

Dissolved organic matter (DOM) sampled from municipal landfill leachate of different ages with/without anoxic or aerobic treatment, was intensively fractionated via size exclusion chromatography (SEC) and hydrophobic resins, and was studied with fluorescence excitation and emission matrix (EEM). Six fluorophores with multiple EEM peaks (fluorophore A-F) were identified based on the collected EEM spectra and validated by bi-variate analysis, principal component analysis, and parallel factor analysis, as follows (excitation wavelength Ex and emission wavelength Em): (Ex 240, 310, 360 nm, Em 460 nm), (Ex 220, 280 nm, Em 340 nm), (Ex 220, 270 nm, Em 300 nm), (Ex 220, 280 nm, Em 360 nm), (Ex 230, 320 nm, Em 420 nm) and (Ex 220, 310 nm, Em 400 nm). The spectral characteristics of these fluorophores were discussed using fractional EEM and apparent molecular weight (AMW) data obtained via SEC analysis. The triple peak flurophore A was pointed at a hydrophobic acid or hydrophobic neutral compound with a pyrenyl functional group of AMW 2500-3500 Da, which displayed an excitation wavelength at 360 nm and a fluorescence intensity ratio of 6.70(+/-1.79):1.70(+/-0.41):1 (fluorescent intensities of Ex 240:Ex 310:Ex 360 nm at Ex 460 nm). This compound is observed to be refractory in landfilling or in anoxic/aerobic treatments, and is specific to this leachate contamination. This paper revealed that the coupling of SEC and EEM can be useful to track the fluorescent DOM fraction in landfill leachate.

Multivariate methods on the excitation emission matrix fluorescence spectroscopic data of diesel–kerosene mixtures: A comparative study

Quantitative determination of kerosene fraction present in diesel has been carried out based on excitation emission matrix fluorescence (EEMF) along with parallel factor analysis (PARAFAC) and N-way partial least squares regression (N-PLS). EEMF is a simple, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. Calibration models consisting of varying compositions of diesel and kerosene were constructed and their validation was carried out using leave-one-out cross validation method. The accuracy of the model was evaluated through the root mean square error of prediction (RMSEP) for the PARAFAC, N-PLS and unfold PLS methods. N-PLS was found to be a better method compared to PARAFAC and unfold PLS method because of its low RMSEP values.