光谱学与光谱分析 |
|
|
|
|
|
Using Three-Dimensional Fluorescence Spectrum Technology to Analyze the Effects of Natural Dissolved Organic Matter on the Pesticide Residues in the Soil |
LEI Hong-jun, PAN Hong-wei*, HAN Yu-ping, LIU Xin, XU Jian-xin |
Center of Water Resources Efficient Utilization and Guarantee Engineering, Zhengzhou 450011, China |
|
|
Abstract The behavior of pesticide in soil is influenced by dissolved organic matter (DOM) through competition adsorption, adsorption, solubilization, accelerated degradation, and so on. Thus DOM and its components play an important role in the environmental risk in the soil ecosystem and groundwater environment. Currently, most studies focused on the short-term effect of high concentration of DOM on the pesticide residues. However, soil DOM is mainly at low level. Therefore, there is of some practical significance to probe into the environmental behavior of soil pesticides under natural level of DOM. Thus a site investigation was conducted in the farmland with long-term application history of pesticide. By using the three dimensional excitation-emission fluorescence matrix (3D-EEM) technology, together with the fluorescence regional integration (FRI) quantitative method, the long-term effects of pesticide residues under low concentration of natural DOM were analyzed. Results showed that: (1) The long-term effects of the natural DOM components on the environment behavior of most soil organo-chlorine pesticides were not significant except for a few pesticides such as γ-HCH, p,p’-DDE, etc. (2) The influencing effects of DOM components on different type of pesticides were varied. Among which, the content of tyrosine component showed a significantly negative correlation (p<0.05) with the concentration of γ-HCH and p,p’-DDE. There were significant positive correlations (p<0.05) between the by-products of microbial degradation in DOM components and the concentration of heptachlor. There were also a significant positive correlation (p<0.05) between the content of active humus component of humic acid in the DOM and the concentration of heptachlor epoxide. These results suggested that the distribution of different types of pesticides residue in the soil was influenced by different components at different levels of significance. (3) The humification degree of soil organic matter showed minor effect of DOM on the pesticide residues in the soil. In this study, 3D-EEM and FRI technology were firstly coupled in use for studying the influence of different components of DOM in soil on the environmental behavior of pesticides, which provides a new idea for the research on the mechanism of pesticides transportation and transformation in soil and groundwater environment.
|
Received: 2014-07-30
Accepted: 2014-10-12
|
|
Corresponding Authors:
PAN Hong-wei
E-mail: phw103@163.com
|
|
[1] Noshadi M, Jamshidi S. Agricultural Water Management, 2014, 143: 38. [2] Blasioli S, Braschi I, Pinna M V, et al. Journal of Agricultural and Food Chemistry, 2008, 56(11): 4102. [3] Xing B S. Massachusetts: Water Resources Research Center Publication, 2006: 180. [4] Nelson S D, Farmer W J, Letey J, et al. Journal of Environmental Quality, 2000, 29(6): 1856. [5] Lee D Y, Farmer J. Journal of Environmental Quality, 1989, 18(4): 468. [6] Flores-Céspedes F, Fernández-Pérez M, Villafranca-Sánchez M, et al. Environmental Pollution, 2006, 142(3): 449. [7] Wei Z, Zhao X, Zhu C, et al. Chemosphere, 2014, 95: 261. [8] Pan H, Lei H, Xi B, et al. Spectroscopy and Spectral Analysis, 2014, 34(6): 1582. [9] Tang S, Wang Z, Wu Z, et al. Journal of hazardous Materials, 2010, 178(1-3): 377. [10] Coble P G. Marin Chemistry, 1996, 51(4): 325. [11] Yu H, Xi B, Su J, et al. Soil Science, 2010, 175(5): 240. [12] Spark K M, Swift R S. Science of the Total Environment, 2002, 298(1): 147. [13] Barriuso E, Baer U, Caiver R. Journal of Environmental Quality, 1992, 21(3): 359. [14] Barriuso E, Houot S. Chemosphere, 1998, 37(6): 1091. [15] Li K, Xing B, Torello W A. Environmental Pollution, 2005, 134(2): 187. |
[1] |
XU Tian1, 2, LI Jing1, 2, LIU Zhen-hua1, 2*. Remote Sensing Inversion of Soil Manganese in Nanchuan District, Chongqing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 69-75. |
[2] |
LEI Hong-jun1, YANG Guang1, PAN Hong-wei1*, WANG Yi-fei1, YI Jun2, WANG Ke-ke2, WANG Guo-hao2, TONG Wen-bin1, SHI Li-li1. Influence of Hydrochemical Ions on Three-Dimensional Fluorescence
Spectrum of Dissolved Organic Matter in the Water Environment
and the Proposed Classification Pretreatment Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 134-140. |
[3] |
GU Yi-lu1, 2,PEI Jing-cheng1, 2*,ZHANG Yu-hui1, 2,YIN Xi-yan1, 2,YU Min-da1, 2, LAI Xiao-jing1, 2. Gemological and Spectral Characterization of Yellowish Green Apatite From Mexico[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 181-187. |
[4] |
LI Hu1, ZHONG Yun1, 2, FENG Ya-ting1, LIN Zhen1, ZHU Shi-jiang1, 2*. Multi-Vegetation Index Soil Moisture Inversion Model Based on UAV
Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 207-214. |
[5] |
HAN Xue1, 2, LIU Hai1, 2, LIU Jia-wei3, WU Ming-kai1, 2*. Rapid Identification of Inorganic Elements in Understory Soils in
Different Regions of Guizhou Province by X-Ray
Fluorescence Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 225-229. |
[6] |
MENG Shan1, 2, LI Xin-guo1, 2*. Estimation of Surface Soil Organic Carbon Content in Lakeside Oasis Based on Hyperspectral Wavelet Energy Feature Vector[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3853-3861. |
[7] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
[8] |
CHENG Hui-zhu1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, MA Qian1, 2, ZHAO Yan-chun1, 2. Genetic Algorithm Optimized BP Neural Network for Quantitative
Analysis of Soil Heavy Metals in XRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3742-3746. |
[9] |
SONG Yi-ming1, 2, SHEN Jian1, 2, LIU Chuan-yang1, 2, XIONG Qiu-ran1, 2, CHENG Cheng1, 2, CHAI Yi-di2, WANG Shi-feng2,WU Jing1, 2*. Fluorescence Quantum Yield and Fluorescence Lifetime of Indole, 3-Methylindole and L-Tryptophan[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3758-3762. |
[10] |
YANG Ke-li1, 2, PENG Jiao-yu1, 2, DONG Ya-ping1, 2*, LIU Xin1, 2, LI Wu1, 3, LIU Hai-ning1, 3. Spectroscopic Characterization of Dissolved Organic Matter Isolated From Solar Pond[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3775-3780. |
[11] |
XIE Peng, WANG Zheng-hai*, XIAO Bei, CAO Hai-ling, HUANG Yi, SU Wen-lin. Hyperspectral Quantitative Inversion of Soil Selenium Content Based on sCARS-PSO-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3599-3606. |
[12] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
[13] |
XUE Fang-jia, YU Jie*, YIN Hang, XIA Qi-yu, SHI Jie-gen, HOU Di-bo, HUANG Ping-jie, ZHANG Guang-xin. A Time Series Double Threshold Method for Pollution Events Detection in Drinking Water Using Three-Dimensional Fluorescence Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3081-3088. |
[14] |
AN Bai-song1, 2, WANG Xue-mei1, 2*, HUANG Xiao-yu1, 2, KAWUQIATI Bai-shan1, 2. Hyperspectral Estimation of Soil Lead Content Based on Random Frog Band Selection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3302-3309. |
[15] |
ZHU Shao-hao1, SUN Xue-ping1, TAN Jing-ying1, YANG Dong-xu1, WANG Hai-xia2*, WANG Xiu-zhong1*. Study on a New Sensing Method of Colorimetric and Fluorescence Dual Modes for Pesticide Residue[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2785-2791. |
|
|
|
|