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基于三维荧光光谱和正定矩阵因子模型的上塘河(海宁段)污染源解析
Source Apportionment of Shangtang River (Haining Section) Based on Three-Dimensional Fluorescence Spectroscopy and Positive Matrix Factorization Model
投稿时间:2025-01-24  修订日期:2025-11-22
DOI:10.19316/j.issn.1002-6002.2026.02.22
中文关键词:  三维荧光光谱  平行因子分析  正定矩阵因子  污染溯源
英文关键词:EEM  PARAFAC  PMF  source apportionment
基金项目:
作者单位E-mail
邵一泓 嘉兴市海宁生态环境监测站, 浙江 嘉兴 314000  
赖欣 四川省生态环境监测总站, 四川 成都 610091 183296955@qq.com 
刘丰羽 中国环境监测总站, 北京 100012  
朱怡苹 嘉兴市海宁生态环境监测站, 浙江 嘉兴 314000  
潘礼斌 嘉兴市海宁生态环境监测站, 浙江 嘉兴 314000  
陆金业 嘉兴市海宁生态环境监测站, 浙江 嘉兴 314000  
许秀艳 中国环境监测总站, 北京 100012  
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中文摘要:
      江浙地区平原河网分布密集,单一溯源方法较难厘清复合污染河流污染源状况。基于水质、水文气象、沉积物数据,利用三维荧光光谱(EEM)、平行因子分析(PARAFAC)解析水体荧光有机物主要来源、组分,以优化正定矩阵因子(PMF)模型输出,实现对污染源的定性定量解析,结果显示:研究区域水体4个主要荧光组分中,C1、C4类腐殖质与城镇点源、工业点源、农业面源的氮磷营养盐和有机污染指标排放有关,C2、C3类蛋白质与生产生活的氮磷排放有关。各污染源贡献占比分别为城镇点源(25.2%)、农业种植面源-内源混合源(23.2%)、城镇生活-农业生产-工业排放混合源(19.8%)、内源(16.4%)、农业面源(15.4%)。
英文摘要:
      The Jiangsu and Zhejiang regions are characterized by dense plain river networks,making it difficult to clarify the pollution sources of composite polluted rivers using a single tracing method.Based on data from water quality,hydro-meteorology,and sediments,the study employed three-dimensional fluorescence spectroscopy (EEM) and parallel factor analysis (PARAFAC) to identify the main sources and components of fluorescent organic matter in the water.This approach optimized the outputs of the Positive Matrix Factorization (PMF) model,enabling qualitative and quantitative analysis of pollution sources.The results indicated that among the four major fluorescent components of water bodies in the study area,C1 and C4 humic substances were related to the discharge of nitrogen and phosphorus nutrients and organic pollution indicators from urban point sources,industrial point sources and agricultural non-point sources.C2 and C3 protein substances were associated with nitrogen and phosphorus emissions from production and domestic activities.The contribution ratios of various pollution sources were as follows: urban point sources (25.2%),mixed source of agricultural non-point-internal mixed sources (23.2%),mixed sources of urban living,agricultural production and industrial emissions (19.8%),internal sources (16.4%),and agricultural non-point sources (15.4%).
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