- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Monitoring of polycyclic aromatic hydrocarbon contamination at four oil spill sites using fluorescence spectroscopy coupled with parallel factor-principal component analysis
摘要： Fluorescence spectroscopy analysis of oil and environmental samples collected from four oil spill incidents in Canada—a 2016 pipeline spill into the North Saskatchewan River (NSR), Saskatchewan; a 2015 train derailment in Gogama, Ontario; the 1970 sinking of the SS Arrow ship in Chedabucto Bay, Nova Scotia; and the 1970 sinking of the Irving Whale barge in the Gulf of St. Lawrence—permitted assessment of the PAH content of environmentally weathered samples. A recently developed fluorescence fingerprinting model based on excitation–emission matrix-parallel factor analysis-principal component analysis (EEM-PARAFAC-PCA) was applied to (i) evaluate the intensity of the abundant PAH groups in the samples, (ii) investigate changes in the PAH composition of environmental samples over time due to weathering, and (iii) classify the original spilled oil and environmental samples within the already established classes of the fingerprinting PCA model. The environmental sediment samples collected from the Husky Energy spill site show loss of PAHs occurring over the course of 15 months post-spill. However, the extent of weathering depends on several environmental factors rather than solely the time of weathering, the PAH loss was maximum at 15 months. There was a decrease in the PAH content of the environmental samples of Gogama spill collected 20 months post-spill. Almost all of Gogama environmental sediment samples underwent substantial weathering, making PCA classification impractical. The SS Arrow and Irving Whale samples fell within adjacent PCA groups, as they both had a similar type of spilled oil (Bunker C) with similarity in chemical composition.
关键词： EEM-PARAFAC-PCA,fluorescence spectroscopy,environmental monitoring,oil spill,PAH contamination
更新于2025-11-19 16:56:42
-
Characterizing the transformation of aquatic humic substances exposed to ultraviolet radiation using excitation–emission matrix fluorescence spectroscopy and PARAFAC
摘要： It is important to understand the change in aquatic humic substances (AHS) induced by light due to the upward trend in ultraviolet (UV) radiation reaching the surface of the Earth. Changes in the quantity and quality of AHS in AHS-rich wetland water exposed to UV-A or UV-B light were determined using 3-dimensional excitation–emission matrix (EEM) fluorescence spectroscopy combined with parallel factor analysis (PARAFAC) and a resin isolation method. The dissolved organic carbon and AHS-carbon concentrations decreased via photodegradation with UV-A or UV-B exposure. The decreases in both carbon concentrations were greater when exposed to UV-B than when exposed to UV-A. Three AHS-like components were detected by EEM-PARAFAC: AHS-1, AHS-2, and AHS-3. AHS-1 and AHS-3 were degraded more by UV-A and UV-B exposure, respectively. AHS-2 was degraded slightly by UV-A exposure, whereas exposure to UV-B generated AHS-2 in the presence of low-molecular-weight compounds, and then underwent photodegradation. AHS-1 exposed to UV-A and AHS-3 exposed to UV-A or UV-B photoflocculated at day 14. The humification index indicated that UV-A exposure led to the preferential photodegradation of AHS, whereas UV-B exposure not only caused AHS degradation but also the degradation or photoflocculation of other compounds with simple structures. AHS changed little in the dark, demonstrating that bacterial effects on AHS were relatively unimportant. The processes of humification and flocculation are important in removing and sequestering carbon from its active cycle. Therefore, the degradation and transformation of AHS exposed to UV can have a major impact on aquatic ecosystem processes.
关键词： photochemical degradation,ultraviolet radiation,aquatic humic substances (AHS),EEM-PARAFAC,dissolved organic matter (DOM)
更新于2025-09-23 15:21:01
-
Robust Classification of Tea Based on Multi-Channel LED-Induced Fluorescence and a Convolutional Neural Network
摘要： A multi-channel light emitting diode (LED)-induced fluorescence system combined with a convolutional neural network (CNN) analytical method was proposed to classify the varieties of tea leaves. The fluorescence system was developed employing seven LEDs with spectra ranging from ultra-violet (UV) to blue as excitation light sources. The LEDs were lit up sequentially to induce a respective fluorescence spectrum, and their ability to excite fluorescence from components in tea leaves were investigated. All the spectral data were merged together to form a two-dimensional matrix and processed by a CNN model, which is famous for its strong ability in pattern recognition. Principal component analysis combined with k-nearest-neighbor classification was also employed as a baseline for comparison. Six grades of green tea, two types of black tea and one kind of white tea were verified. The result proved a significant improvement in accuracy and showed that the proposed system and methodology provides a fast, compact and robust approach for tea classification.
关键词： tea,variety,classification,convolutional neural network,EEM,LED,fluorescence
更新于2025-09-16 10:30:52
-
8.78% Efficient All‐Polymer Solar Cells Enabled by Polymer Acceptors Based on a B←N Embedded Electron‐Deficient Unit
摘要： Mono-cardboard waste digestion in batch tests associated with different impact factors was investigated. The maximum methane generation was 394 mL/gVSadd with the best F/M of 0.5 at mesophilic conditions. The highest methane content reached 75% in the dynamic water bath feeding with an average particle size of 1?3 mm. Hydrolysis and methanogenesis were significantly different between static and dynamic states, especially at particle size over 3 mm. The modified Gompertz model (R2 > 0.98) and the modified Aiba model (R2 > 0.88) were the most appropriate models for methane generation among the six kinds of models. At different TS, the variation of dissolved organic matters reflects the metabolic rate of the microbial community. The soluble microbial product-like and protein-like components half split by excitation?emission factors significantly negatively corresponded to biomethane production. Moreover, a rapid loss of matrix-parallel methanogenesis was observed with high organics concentration. A strong correlation between the F/M ratio and the CH4 generation ability was observed with an optimized F/M of 0.5. The maximum energy production was also investigated based on the optimized particle size of 2?5 mm and F/M of 0.5, in which long-term stability was maintained.
关键词： dissolved organic matter,kinetic models,methane production,EEM-PARAFAC,Mono-cardboard digestion
更新于2025-09-11 14:15:04
-
Characterization and bioavailability of rainwater dissolved organic matter at the southeast coast of China using absorption spectroscopy and fluorescence EEM-PARAFAC
摘要： Rainwater brings considerable amounts of dissolved organic matter (DOM) from atmosphere to freshwater and marine environments, but little is known about the chemical composition and bioavailability of rainwater DOM. The quantity, quality, and bioavailability of DOM were investigated for 21 rain events at a coastal site in southeast China, using dissolved organic carbon (DOC) measurements, absorption spectroscopy, and fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC). The DOC concentration ranged from 35 to 457 μM, which was affected by the prevailing monsoon, rainfall amount and terrestrial/anthropogenic inputs. The volume-weighted average DOC was 118 μM, corresponding to a rainwater DOC flux of 1.98 g m?2 yr?1. Four fluorescent components were identified with EEM-PARAFAC, including three humic-like components (C1-C3) and one tyrosine-like component C4. Absorption coefficient (aCDOM(300)) and fluorescence intensities of C2-C4 strongly correlated with DOC, indicating they can be used for DOC estimation. Rainwater DOM was characterized by low DOC-specific UV absorbance (SUVA254) and humification index (HIX), which indicated a low aromaticity and humification degree. Principal component analysis (PCA) based on DOM indices revealed two principal factors, which were related to the DOM concentration and humification degree respectively. PCA, together with air-mass trajectory analysis, successfully separated different rain events with variable inputs from living plants/local sources, soil organic matter/humified materials, and the marine source. Rainwater DOM generally showed a high bioavailability of 50% ± 19%, with higher degradability of non-chromophoric constituents and C1-C2 than other components. This study demonstrated the applicability of absorption and EEM-PARAFAC combined with PCA and air-mass trajectory analysis in differentiating rain events and tracking organic matter sources, and revealed different effects of microbial degradation on individual PARAFAC components in rainwater.
关键词： Dissolved organic matter,Absorption spectroscopy,EEM-PARAFAC,Rainwater,Bioavailability
更新于2025-09-10 09:29:36
-
Fluorescence spectra predict microcystin-LR and disinfection byproduct formation potential in lake water
摘要： Disinfection byproducts (DBPs) and algal toxins can be expensive to monitor and represent significant potential risks to human health. DBPs, including haloacetic acids and trihalomethanes, are possible or probable human carcinogens. Microcystin-LR—produced by cyanobacteria—is linked with various adverse health effects. Here we show that fluorescence spectra predict both microcystin-LR occurrence and DBP formation potential (DBPfp) in lake water. We compared models with either fluorescence spectra or a suite of water quality predictors as inputs. A regularized logistic regression model with fluorescence spectral inputs correctly classified 94% of test data with respect to microcystin-LR occurrence, with a 96% probability of correctly ranking a detect/non-detect pair. Regularized linear regression predicted DBPfp based on fluorescence inputs with a combined R2 of 0.83 on test data. A gradient-boosted classifier with seven water quality inputs was comparable in detecting microcystin-LR (91% correct), as was UV254 in predicting DBPfp (combined test R2 = 0.84), but no single parameter matched fluorescence spectra over both predictive tasks. Results highlight the potential for multiparameter monitoring via fluorescence spectroscopy, extending previous work on predicting DBPs alone. As a high-frequency monitoring tool, this approach could supplement mass spectrometric methods that may only be applicable at low frequency due to resource limitations.
关键词： cyanobacteria,MC-LR,trihalomethanes,elastic net,EEM,classification,gradient boosting,haloacetic acids,lasso
更新于2025-09-04 15:30:14