Excitation Emission Matrix Fluorescence Spectroscopy for Combustion Generated Particulate Matter Source Identification

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.

Evolution of the chromophore aerosols and its driving factors in summertime Xi'an, Northwest China

Atmospheric chromophores have photo-sensitiveness that can participate in photochemical reactions, so they may have the potential to make an important contribution in organic aerosols aging. This study attempts to explain the effects of oxidation reaction and photochemical reaction on atmospheric chromophores. For this study, the summer period (higher sunshine intensity) was selected to observe the mechanisms by the online excitation emission matrix (EEM) fluorescence. The results showed that a lot of secondary organic aerosols were produced in the afternoon, but a large portion of them is non-chromophore. We observed that the secondary chromophores of highly-oxygenated humic-like substances (HULIS) were produced, which suggests a degradation product of less-oxygenated HULIS. The photochemical reaction and oxidation reaction were the important reactions that occur in the afternoon, which drives the oxidation state evolution of the atmospheric chromophores. Atmospheric oxidation processes are the mainly driving reaction for the transformation of atmospheric chromophore. The aged aerosol has a lower fluorescence index and a high degree of humification. It is speculated that the aerosol from night to morning is in the accumulation process dominated by local sources, and then it is mainly in the process of being gradually aged at noon and afternoon. This study will guide to better understand the atmospheric chemical processes of chromophore aerosols and provide guidance for the EEM approach to trace the aerosol aging in the atmosphere.

Diurnal evolutions and sources of water-soluble chromophoric aerosols over Xi'an during haze event, in Northwest China

Atmospheric brown carbon and their chemical behavior potentially impacts the climate and air quality. Due to lack of researches on the atmospheric chromophores by using online experimental instrument, so using the offline EEM approaches to study their types, sources and chemical processes. In this study, PILS-EEM-TOC system (Particle into liquid sampler coupled with excitation-emission matrix and total organic carbon) was developed in order to distinguish the hourly evolutions and sources of water-soluble chromophoric organic matters in atmospheric fine particles. The results suggested that the sources of atmospheric chromophores in winter were primary combustion (~90%) and coal burning, followed by biomass burning and cooking emissions in Xi'an (Northwest China). These atmospheric chromophores decay under the combined action of solar radiation and atmospheric oxidants. Meanwhile, the secondary chromophores were mainly highly-oxygenated humic-like substance (HULIS), produced by atmospheric oxidation reactions with the highest peak in the afternoon. The partly secondary chromophores can also be generated through the Maillard-like reaction in the morning, which depends on the relative humidity of the atmosphere. These findings made a deeper understanding of the sources and transformation of atmospheric brown carbon aerosols.

Solid-phase excitation-emission matrix spectroscopy for chemical analysis of combustion aerosols

Exposure to ultrafine combustion aerosols such as particulate matter (PM) from residential woodburning, forest fires, cigarette smoke, and traffic emission have been linked to adverse health outcomes. Excitation-emission matrix (EEM) spectroscopy presents a sensitive and cost-effective alternative for analysis of PM organic fraction. However, as with other analytical chemistry methods, the miniaturization is hindered by a solvent extraction step and a need for benchtop instrumentation. We present a methodology for collecting and in-situ analysis of airborne nanoparticles that eliminates labor-intensive sample preparation and miniaturizes the detection platform. Nanoparticles are electrostatically collected onto a transparent substrate coated with solid-phase (SP) solvent-polydimethylsiloxane (PDMS). The PM organic fraction is extracted into PDMS and analyzed in-situ, thus avoiding liquid-phase extraction. In the SP-EEM analysis, we evaluated external and internal excitation schemes. Internal excitation shows the lowest scattering interference but leads to signal masking from PDMS fluorescence for λ<250nm. The external excitation EEM spectra are dependent on the excitation light incident angle; ranges of 30-40° and 55-65° show the best results. SP-EEM spectra of woodsmoke and cigarette smoke samples are in good agreement with the EEM spectra of liquid-phase extracts. The SP-EEM technique can be used to develop wearable sensors for exposure assessments and environmental monitoring.

Exploration of total synchronous fluorescence spectroscopy combined with pre-trained convolutional neural network in the identification and quantification of vegetable oil

In order to distinguish different vegetable oils, adulterated vegetable oils, and to identify and quantify counterfeit vegetable oils, a method based on a small sample size of total synchronous fluorescence (TSyF) spectra combined with convolutional neural network (CNN) was proposed. Four typical vegetable oils were classified by three ways of fine-tuning the pre-trained CNN, the pre-trained CNN as a feature extractor, and traditional chemometrics. The pre-trained CNN was combined with support vector machines to distinguish adulterated sesame oil and counterfeit sesame oil separately with 100% correct classification rates. The pre-trained CNN combined with partial least square regression was used to predict the level of counterfeit sesame oil. The coefficient of determination for calibration (R_c²) values were all greater than 0.99, and the root mean square errors of validation were 0.81% and 1.72%, respectively. These results show that it is feasible to combine TSyF spectra with CNN for vegetable oil identification.

Excitation-Emission Matrix Spectroscopy for Analysis of Chemical Composition of Combustion Generated Particulate Matter

Analysis of particulate matter (PM) is important for the assessment of human exposures to potentially harmful agents, notably combustion-generated PM. Specifically, polycyclic aromatic hydrocarbons (PAHs) found in ultrafine PM have been linked to cardiovascular diseases and carcinogenic and mutagenic effects. In this study, we quantify the presence and concentrations of PAHs with lower molecular weight (LMW, 126 < MW < 202) and higher molecular weight (HMW, 226 < MW < 302), i.e., smaller and larger than Pyrene, in combustion-generated PM using excitation-emission matrix (EEM) fluorescence spectroscopy. Laboratory combustion PM samples were generated in a laminar diffusion inverted gravity flame reactor (IGFR) operated on ethylene and ethane. Fuel dilution by Ar in 0% to 90% range controlled the flame temperature. The colder flames result in lower PM yields however, the PM PAH content increases significantly. Temperature thresholds for PM transition from low to high organic carbon content were characterized based on the maximum flame temperature (T_max,c ∼ 1791 to 1857 K) and the highest soot luminosity region temperature (T*_c ∼ 1600 to 1650K). Principal component regression (PCR) analysis of the EEM spectra of IGFR samples correlates to GCMS data with R² = 0.988 for LMW and 0.998 for HMW PAHs. PCR-EEM analysis trained on the IGFR samples was applied to PM samples from woodsmoke and diesel exhaust, the model accurately predicts HMW PAH concentrations with R² = 0.976 and overestimates LMW PAHs.