Feasibility of the simultaneous determination of polycyclic aromatic hydrocarbons based on two-dimensional fluorescence correlation spectroscopy

Deciphering DOM-metal binding using EEM-PARAFAC: Mechanisms, challenges, and perspectives

Dissolved organic matter (DOM) is a pivotal component of the biogeochemical cycles and can combine with metal ions through chelation or complexation. Understanding this process is crucial for tracing metal solubility, mobility, and bioavailability. Fluorescence excitation emission matrix (EEM) and parallel factor analysis (PARAFAC) has emerged as a popular tool in deciphering DOM-metal interactions. In this review, we primarily discuss the advantages of EEM-PARAFAC compared with other algorithms and its main limitations in studying DOM-metal binding, including restrictions in spectral considerations, mathematical assumptions, and experimental procedures, as well as how to overcome these constraints and shortcomings. We summarize the principles of EEM to uncover DOM-metal association, including why fluorescence gets quenched and some potential mechanisms that affect the accuracy of fluorescence quenching. Lastly, we review some significant and innovative research, including the application of 2D-COS in DOM-metal binding analysis, hoping to provide a fresh perspective for possible future hotspots of study. We argue the expansion of EEM applications to a broader range of areas related to natural organic matter. This extension would facilitate our exploration of the mobility and fate of metals in the environment.

Separation of the overlapped humic acid and BGP characteristic peaks using two-dimensional correlation fluorescence-UV-vis spectroscopy

Fluorescence spectroscopy has been widely used to detect polycyclic aromatic hydrocarbons (PAHs) in the environment. However, the interference of coexisting humic acids (HA) in the environment poses a great challenge to the qualitative and quantitative detection of PAHs using fluorescence spectroscopy. In this study, the spectral properties of benzo [ghi] perylene (BGP) and HA were investigated based on fluorescence and UV-vis spectroscopy combined with two-dimensional (2D) correlation analysis. Under the external disturbance of HA concentration, the homo-2D (fluorescence, UV-visible) correlation and hetero-2D fluorescence-UV-visible correlation spectral characteristics of the mixed samples of HA and BGP were studied, and the effect of HA on the fluorescence of BGP was investigated. It can be inferred that the fluorescence peak at 478 nm come from BGP, and the fluorescence peaks at 442 nm and 533 nm, UV absorption peak at 233 nm come from HA. Meanwhile, asynchronous two-trace two-dimensional (2T2D) fluorescence correlation slice spectra at 533 nm were obtained. The slice spectral intensity at 478 nm was extracted to quantify the BGP concentration in mixture. The results showed that the slice spectral intensity and BGP concentration had a good linear relationship with the coefficient of determination R² = 0.96. This research provides a way to further study the separation method of HA and PAHs or explore the correction method of the effect of HA on PAHs.

Investigation of the Interaction of Benzo(a)Pyrene and Fluoranthene with Cucurbit[n]urils (n = 6-8): Experimental and Molecular Dynamic Study

The inclusion complexes of cucurbit[n]uril, CB[n] (n = 6-8), with poly aromatic hydrocarbon (PAH) Benzo(a)Pyrene (BaP), and fluoranthene (FLT) were investigated carefully in aqueous media. Fluorescence and ¹H NMR spectroscopy were used to characterize and investigate the inclusion complexes that were prepared in the aqueous media. The most predominant complexes of both guests with hosts were the 1:1 guest: host complexes. Stability constants of 2322 ± 547 M^-1, 7281 ± 689 M^-1, 3566 ± 473 M^-1 were obtained for the complexes of BaP with CB[6], CB[7], and CB[8], respectively. On the other hand, stability constants of 5900.270 ± 326 M^-1, 726.87 ± 78 M^-1, 3327.059 ± 153 M^-1 were obtained for the complexes of FLT with CB[6], CB[7], and CB[8], respectively. Molecular dynamic (MD) simulations were used to study the mode and mechanism of the inclusion process and to monitor the stability of these complexes in aqueous media at an atomistic level. Analysis of MD trajectories has shown that both BaP and FLT form stable inclusion complexes with CB[7] and CB[8] in aqueous media throughout the simulation time, subsequently corroborating the experimental results. Nevertheless, the small size of CB[6] prohibited the encapsulation of the two PAHs inside the cavity, but stable exclusion complex was observed between them. The main driving forces for the stability of these complexes are the hydrophobic forces, van der Waals interactions, electrostatic effect, the π····π and C-H···π interaction. These results suggest that BaP and FLT can form stable complexes with CB[n] (n = 6-8) in solution.

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model†

Polycyclic aromatic hydrocarbons (PAHs) are typical organic pollutants in soil and are teratogenic and carcinogenic. Therefore, rapid and accurate analysis of PAHs in soil can provide a theoretical basis and data support for soil contamination risk assessment. In this work, a fluorescence spectroscopy technique combined with partial least squares (PLS) was proposed for rapid quantitative analysis of phenanthrene (PHE) in soil. At first, the fluorescence spectra of 29 soil samples with different concentrations (0.3–10 mg g⁻¹) of PHE were collected by RF-5301 PC fluorescence spectrophotometer. Secondly, the effects of different spectral preprocessing methods were investigated on the prediction performance of the PLS calibration model. And then, the influence of competitive adaptive reweighted sampling (CARS) wavelength points on the prediction performance of PLS calibration model was discussed. Finally, according to the selected wavelength points, a quantitative analytical model for PHE content in soil was constructed using the PLS calibration method. To further explore the predictive performance of the CARS-PLS calibration model, the predictive results were compared with those of the RAW spectrum-partial least squares calibration model (RAW-PLS) and the wavelet transform-standard normal variation (WT-SNV) calibration model. The CARS-PLS calibration model showed the optimal predictive performance and its coefficient of determination of cross-validation (R_cv²) and root mean square error of 10-fold cross-validation (RMSEcv) were 0.9957 and 18.98%, respectively. The coefficient of determination of prediction set (R_p²) and root mean square error of prediction set (RMSEp) were 0.9963 and 16.13%, respectively. Hence, the CARS algorithm based on fluorescence spectrum coupled with PLS can give a rapid and accurate quantitative analysis of the PHE content in soil.

Fluorescence spectroscopy coupled with CARS-PLS model is successfully used for the rapid quantitative analysis of phenanthrene in soil.

New Constructed EEM Spectra Combined with N-PLS Analysis Approach as an Effective Way to Determine Multiple Target Compounds in Complex Samples

Excitation-emission matrix (EEM) fluorescence spectroscopy has been applied to many fields. In this study, a simple method was proposed to obtain the new constructed three-dimensional (3D) EEM spectra based on the original EEM spectra. Then, the application of the N-PLS method to the new constructed 3D EEM spectra was proposed to quantify target compounds in two complex data sets. The quantitative models were established on external sample sets and validated using statistical parameters. For validation purposes, the obtained results were compared with those obtained by applying the N-PLS method to the original EEM spectra and applying the PLS method to the extracted maximum spectra in the concatenated mode. The comparison of the results demonstrated that, given the advantages of less useless information and a high calculating speed of the new constructed 3D EEM spectra, N-PLS on the new constructed 3D EEM spectra obtained better quantitative analysis results with a correlation coefficient of prediction above 0.9906 and recovery values in the range of 85.6-95.6%. Therefore, one can conclude that the N-PLS method combined with the new constructed 3D EEM spectra is expected to be broadened as an alternative strategy for the simultaneous determination of multiple target compounds.

A comparative study of three chemometrics methods combined with excitation–emission matrix fluorescence for quantification of the bioactive compounds aesculin and aesculetin in Cortex Fraxini

Cortex Fraxini is an important traditional Chinese herbal medicine with various medical functions. Aesculin and aesculetin are the main effective components of Cortex Fraxini. The fluorescence signals of the two compounds have a high degree of overlap with each other, making quantitative analysis difficult with conventional analytical methods. In the present study, different chemometrics methods, including lasso regression (LAR), interval partial least squares (iPLS), and multidimensional partial least squares (N-PLS) methods, were employed and combined with excitation–emission matrix (EEM) fluorescence for the purpose of accurate quantification of aesculin and aesculetin in Cortex Fraxini samples. The most satisfactory results were obtained by using the N-PLS method based on the EEM spectra without scatterings, with correlation coefficient of calibration and prediction values higher than 0.9972 and 0.9962, respectively, root mean squared errors for calibration and prediction values lower than 0.0304 and 0.1165, respectively, and recovery values in the range of 83.32%–104.62%. The obtained credible models indicated that the N-PLS method combined with EEM spectra has the advantages of being green, low cost, and accurate and it is a good strategy for the determination of active compounds in complex samples. To further confirm the accuracy of the obtained results, the same samples were analyzed by the recognized ultra-performance liquid chromatography method.

A poly(arylene ethynylene)-based microfluidic fluorescence sensor array for discrimination of polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) were discriminated using a microfluidic paper-based sensor array device.

Characterization and treatment of landfill leachate: A review

Landfill leachate is a complicated organic wastewater generated in the sanitary landfilling process. Landfill leachate must be appropriately disposed to avoid ecotoxicity and environmental damage. An in depth understanding of the physiochemical characteristics and environmental behaviors of landfill leachate is essential for its effective treatment. In this study, recent advances on the properties of landfill leachate, its characterization methods and treatment techniques are critically reviewed. Specifically, the up-to-date spectroscopic techniques for landfill leachate characterization and advanced oxidation treatment techniques are highlighted. Moreover, the drawbacks and challenges of current techniques for landfill leachate characterization and treatment are discussed, along with the future perspectives in the development of characterization and treatment approaches for landfill leachate.

Detection of pesticide in water using two-dimensional fluorescence correlation spectroscopy and N-way partial least squares

To determine the concentration of carbaryl and chlorothalonil in water, the potential of two-dimensional (2D) fluorescence correlation spectra with N-way partial least squares (N-PLS) was investigated. A total of 40 mixture solutions of carbaryl and chlorothalonil were prepared and 27 of them were used to form a calibration set. The excitation-emission matrix (EEM) fluorescence spectra of all samples were measured. Under the excitation perturbation, 2D fluorescence correlation spectra of all samples were calculated and formed a 2D correlation spectral matrix. And N-PLS models for determination of carbaryl and chlorothalonil in water were built based on 2D correlation fluorescence spectral matrix and traditional EEM spectral matrix, respectively. Finally, the performances of N-PLS models using both methods were compared. For chlorothalonil, the root mean square error of calibration (RMSEC) were 3.43 × 10^-6 g L^-1 and 5.08 × 10^-6 g L^-1, the root mean square errors of prediction (RMSEP) were 5.86 × 10^-6 g L^-1 and 8.99 × 10^-6 g L^-1 for 2D correlation spectra and EEM spectra, respectively. For carbaryl, the RMSEC were 5.24 × 10^-7 g L^-1 and 6.18 × 10^-7, the RMSEP were 9.20 × 10^-7 g L^-1 and 9.63 × 10^-7 g L^-1 for 2D correlation spectra and EEM spectra, respectively. From the results of this study, it may conclude that 2D fluorescence correlation spectra is superior over the traditional EEM fluorescence spectra in terms of predictability and can be used as an alternative method for detection of organic pollutants in environment.

Recent Advances in Spectroscopy Technology for Trace Analysis of Persistent Organic Pollutants

Persistent organic pollutants (POPs) have attracted significant attention because of their bioaccumulation, persistence, and toxicity. As anthropogenic products, POPs mainly contain polychlorinated biphenyls (PCBs), organochlorine pesticides (OPs), and polycyclic aromatic hydrocarbons (PAHs), and they pose a great threat to human health and the environment. To deal with these toxic contaminants, many different kinds of strategies for sensitively detecting POPs have been developed, such as high performance liquid chromatography (HPLC), surface enhanced Raman spectroscopy (SERS), and fluorescence. This paper mainly summarized the achievements of spectroscopy technologies, which generally consist of SERS, surface plasmon resonance (SPR), and fluorescence, in the detection of low-concentration POPs in different matrices. In addition, a retrospective summary is made on several critical considerations, such as sensitivity, specificity and reproducibility of these spectroscopy technologies in practical applications. Finally, some current challenges and future outlooks for these spectroscopy technologies are provided in regards to environmental analysis.

A green chemometrics-assisted fluorimetric detection method for the direct and simultaneous determination of six polycyclic aromatic hydrocarbons in oil-field wastewaters

Oil-field wastewaters contain high level of polycyclic aromatic hydrocarbons (PAHs), which have to be analyzed to assess the environmental effects before discharge. In this work, a green fluorimetric detection method that combines excitation-emission matrix (EEM) fluorescence with parallel factor analysis (PARAFAC) algorithm was firstly developed to achieve the direct and simultaneous determination of six U.S. EPA PAHs in two different kinds of complex oil-field wastewaters. Due to the distinctive "second-order advantage", neither time-consuming sample pretreatments nor toxic organic reagents were involved in the determination. By using the environment-friendly "mathematical separation" of PARAFAC, satisfactory quantitative results and reasonable spectral profiles for six PAHs were successfully extracted from the total EEM signals of oil-field wastewaters without need of chromatographic separation. The limits of detection of six PAHs were in the range of 0.09-0.72ngmL^-1, and the average spiked recoveries were between (89.4±4.8)% and (109.1±5.8)%, with average relative predictive errors <2.93%. In order to further confirm the accuracy of the proposed method, the same batch oil-field wastewater samples were analyzed by the recognized GC-MS method. t-test demonstrated that no significant differences exist between the quantitative results of the two methods. Given the advantages of green, fast, low-cost and high-sensitivity, the proposed method is expected to be broadened as an appealing alternative method for multi-residue analysis of overlapped PAHs in complex wastewater samples.