光谱学与光谱分析, 2018, 38 (8): 2549, 网络出版: 2018-08-26   

基于3D-EEMs和PARAFAC的土壤渗滤系统DOM垂直分布特征

Vertical Distribution Characteristics of DOM in Soil Infiltration System Based on 3D-EEMs and PARAFAC
作者单位
1 同济大学环境科学与工程学院, 上海 200092
2 中原工学院, 河南 郑州 450007
3 中国环境科学研究院, 北京 100012
4 火箭军后勤科学技术研究所, 北京 100190
摘要
利用三维荧光光谱(3D-EEMs)和平行因子分析(PARAFAC)的方法研究了土壤渗滤系统处理模拟高氨氮废水中溶解性有机物(DOM)的垂直分布特征。 试验在一个中试规模的土壤渗滤系统中进行, 反应器自上而下每隔30 cm设置一个采样口, 采集的样品通过PARAFAC识别出系统不同点位的DOM具有四个荧光组分, 包括两个类腐殖质物质(C1, C2)、 2个类蛋白物质(C3, C4)。 相关性分析显示, 四种荧光组分与多数理化指标呈现极显著性正相关关系, 可以用荧光组分浓度间接表征系统对氮、 磷等营养元素的去除效果。 对荧光组分浓度得分Fmax分析得出, 土壤渗滤系统中类酪氨酸最易降解, 其次为类富里酸、 类胡敏酸类物质, 最难以降解的为类蛋白物质。
Abstract
The vertical distribution characteristics of dissolved organic matter(DOM), which were treated by soil infiltration system with simulated high ammonia nitrogen wastewater, were studied by using three-dimensional excitation emission matrix (3D-EEMs)fluorescence spectroscopy and PARAFAC model. The experiment was carried out on a pilot-scale soil infiltration system with a sampling port at 30 cm intervals from top to bottom. The collected samples were identified with PARAFAC model as having 4 fluorescent components at different points in the system, including two humus substances (C1, C2) and two protein substances (C3, C4) respectively. Correlation analysis showed that there was a significant positive correlation among the four kinds of fluorescence components and most of the physical and chemical indexes. The fluorescence component concentration could indirectly characterize the removal efficiency of nitrogen, phosphorus and other nutrients. The analysis of Fmax showed that tyrosine was the most easily degradable in soil infiltration system, followed by fulvic acid, humic acid and the most difficult to degrade protein.

吕晶晶, 于水利, 张列宇, 席北斗, 窦艳艳, 侯立安. 基于3D-EEMs和PARAFAC的土壤渗滤系统DOM垂直分布特征[J]. 光谱学与光谱分析, 2018, 38(8): 2549. L Jing-jing, YU Shui-li, ZHANG Lie-yu, XI Bei-dou, DOU Yan-yan, HOU Li-an. Vertical Distribution Characteristics of DOM in Soil Infiltration System Based on 3D-EEMs and PARAFAC[J]. Spectroscopy and Spectral Analysis, 2018, 38(8): 2549.

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