研究目的
To study the biodegradable advantages and disadvantages of different types of substances of coking wastewater, classify them into tryptophan-like, tyrosine-like, and humic acid-like components, and evaluate their biodegradability using three-dimensional fluorescence spectrum and PARAFAC model.
研究成果
Three-dimensional fluorescence spectrum combined with PARAFAC model effectively identifies and quantifies organic components in coking wastewater, showing that tryptophan-like components are most biodegradable, followed by tyrosine-like, and humic-like are least biodegradable. Strong correlations between fluorescence intensities and parameters like COD and NH3-N validate the method for biodegradability assessment, providing a reliable tool for wastewater treatment analysis and future research on organic pollutant degradation.
研究不足
The study focuses on coking wastewater from a specific plant, limiting generalizability to other wastewater types. The PARAFAC model requires careful initialization and iteration, which may be computationally intensive. Potential areas for optimization include expanding to diverse wastewater sources and integrating real-time monitoring.
1：Experimental Design and Method Selection:
The study used three-dimensional fluorescence spectrometry and the parallel factors (PARAFAC) model to analyze organic components in coking wastewater before and after A2/O treatment. The design rationale was to identify and quantify fluorescence components (tryptophan-like, tyrosine-like, humic-like) and assess their biodegradability. Theoretical models included PARAFAC decomposition for fluorescence data analysis.
2：Sample Selection and Data Sources:
Wastewater samples were sourced from Shanxi coking plant, China. Samples were collected at different stages (e.g., raw water, secondary sedimentation effluent) and times (S1 to S10). Data included fluorescence spectra and parameters like COD, NH3-N, TP, TN.
3：0). Data included fluorescence spectra and parameters like COD, NH3-N, TP, TN.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Gas chromatograph mass spectrometer Pegasus IV (LECO Corporation), Fluorescence spectrometer FLS1000 (Edinburgh), Ca(OH)2 for pH adjustment, distilled water for blank correction, cutoff optical filter (290 nm).
4：Experimental Procedures and Operational Workflow:
Wastewater was diluted 50 times, pH adjusted to
5：0 with Ca(OH)3D EEMs scan performed using FLS1000 with parameters:
excitation wavelength 250-450 nm, emission wavelength 300-550 nm, wavelength interval 5 nm, PMT voltage 600 V, scanning speed 2400 nm/min. Raman and Rayleigh scattering eliminated by subtracting distilled water spectrum and using optical filter. PARAFAC analysis applied to decompose fluorescence data using Matlab R2012b.
6：2b.
Data Analysis Methods:
5. Data Analysis Methods: PARAFAC model used to decompose fluorescence data into excitation, emission, and score matrices. Core consistency and residual analysis determined component numbers. Fluorescence intensities correlated with COD, NH3-N, TP, TN using statistical methods (implied by correlation coefficients in Table 2).
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