Analysis on influencing factors of detecting chemical oxygen demand in water by three-dimensional spectroscopy
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1. Inner Mongolia Autonomous Region Joint Laboratory of Nuclear and Radiation Detection, College of Physics and Electronic Information, Inner Mongolia Minzu University, Tongliao 028000, China;2. College of Information Engineering, Jingzhou University, Jingzhou 434000, China;3. Alxa League Meteorological Bureau, Alxa 750300, China

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    Abstract:

    This paper focuses on the standard chemical oxygen demand (COD) liquid and studies the impact of pH, nitrite nitrogen, nitrate nitrogen, heavy metals, salinity, and other factors on fluorescence intensity and fluorescence peak positions during the detection of COD in water using fluorescence spectrometry. The influence mechanisms of different environmental factors on fluorescence spectra are also analyzed. Results indicate that pH value affects the fluorescence emission wavelength (Em), resulting in a red shift from 1.5 to 7.2, and a blue shift from 7.2 to 12.3. Nitrate nitrogen can react with organic matter in water to form nitro compounds, leading to a decrease in fluorescence intensity. Salinity has a negligible effect on T1 peak but a relatively large effect on T2 peak. Heavy metal ion concentration has a significant impact on T2 peak, while T1 peak position shifts with an increase in heavy metal ions. This study aims to explore the factors that can impact the detection of COD in water using three-dimensional fluorescence spectrometry, providing references to improve accuracy and practicability for COD detection based on three-dimensional fluorescence spectrometry.

    Reference
    [1] DONG X X, YANG F W, YU H, et al. Study on rapid nondestructive detection of pork lean freshness based on Raman spectroscopy[J]. Spectroscopy and spectral analysis, 2023, 43(2):484-488.
    [2] YAN W H, YANG X Y, GENG X, et al. Rapid identification of fish products using handheld laser induced breakdown spectroscopy combined with random forest[J]. Spectroscopy and spectral analysis, 2022, 42(12):3714-3718.
    [3] HU G T, SHANG H W, TAN R H, et al. Research on model transfer method of organic matter content estimation of different soils using VNIR spectroscopy[J]. Spectroscopy and spectral analysis, 2022, 42(10):3148-3154.
    [4] LI F S, ZENG X L. Quantitative analysis method of soil elements combining sensitivity dimensionality reduction and support vector regression[J]. Laser & optoelectronics progress, 2023, 60(5):0530002.
    [5] CHENG Z, ZHAO N J, YIN G F, et al. Identification of algae community discrete three-dimensional fluorescence spectrum based on SWTATLD[J]. Acta optica
    sinica, 2021, 41(14):1430001. (in Chinese)
    [6] LI F X, TANG B, ZHAO M F, et al. Research on correction method of water quality ultraviolet-visible spectrum data based on compressed sensing[J]. Journal of spectroscopy, 2021, 2021:6650630.
    [7] LI Y, LUO H, FAN X, et al. Open craniocerebral hematoma imaging based on near-infrared spectroscopy[J]. Laser physics letters, 2022, 19(4):045601.
    [8] GAO X Y, ZHANG Z S Y, LU C C, et al. Quantitative analysis of hemoglobin based on SiPLS-SPA wavelength optimization[J]. Spectroscopy and spectral analysis, 2023, 43(1):50-56.
    [9] NAN D N, DONG L Q, FU W X, et al. Fast identification of hazardous liquids based on Raman spectroscopy[J]. Spectroscopy and spectral analysis, 2021, 41(6):1806-1810.
    [10] HUO W, WANG J F, LIU Y R. Spectral pattern recognition and traceability analysis of human fingernail based on machine learning[J]. Laser & optoelectronics progress, 2022, 59(18):1830002.
    [11] DONG Q, WANG W, CAO X, et al. Plasmonic nanostructure characterized by deep-neural-network-
    assisted spectroscopy[J]. Chinese optics letters, 2023, 21(1):010004.
    [12] ZHENG X F, LI C, FAN X Y, et al. Influence of temperature and turbidity on Rhodamine B tracer detection and correction[J]. Infrared and laser engineering, 2022, 51(12):20220243.
    [13] LI F X, TANG B, ZHAO M F, et al. Research on correction method of water quality ultraviolet-visible spectrum data based on compressed sensing[J]. Journal of spectroscopy, 2021, 2021:6650630.
    [14] ZHOU K P, LIU Z Y, CONG M L, et al. Detection of chemical oxygen demand in water based on UV absorption spectroscopy and PSO-LSSVM algorithm[J]. Optoelectronics letters, 2022, 18(4):251-256.
    [15] ZHOU K P, LIU S S, CUI J, et al. Detection of chemical oxygen demand (COD) of water quality based on fluorescence emission spectra[J]. Spectroscopy and spectral analysis, 2020, 40(4):1143-1148.
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ZHOU Kunpeng, LIU Zhiyang, CONG Menglong,,MAN Shanxin. Analysis on influencing factors of detecting chemical oxygen demand in water by three-dimensional spectroscopy[J]. Optoelectronics Letters,2024,20(1):42-47

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History
  • Received:May 06,2023
  • Revised:June 30,2023
  • Online: December 25,2023
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