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基于NMF与CMB耦合应用的水体污染源解析方法 被引量:8

Apportionment techniques of water pollution sources by coupling the model of chemical mass balance and the procedure of nonnegative matrix factorization
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摘要 通过定量方法筛选出特征污染物,开展污染源解析,这是进行环境质量评估、环境风险评价、污染物削减的重要依据,也是切实有效地控制污染,保障环境安全的重要前提.化学质量平衡模型和非负约束因子分析模型是污染源解析中较为有效的两种方法,各自具有特定的应用优势,但同时也都存在一定的应用局限性.通过非负约束因子模型与化学质量模型的耦合应用,充分利用非负约束因子模型反推出线性无关的主要污染源指纹图谱,再利用成熟的化学质量模型得出较为精准的污染源贡献率,可以得到较为准确、合理的应用解.应用实例表明,与单独利用因子模型比较,耦合模型得出的因子载荷矩阵、因子得分矩阵与实际情况更为吻合,污染源贡献率计算更为准确. Using quantitative methods to screen characteristic pollutants and identify pollution sources is an important basis for environmental quality assessment,environmental risk assessment and pollutant mitigation. They are also essential for effective pollution control and environmental protection. Chemical mass balance and factor analysis with nonnegative constraints are two of the effective models to identify pollution sources and they have their advantages and limitations in practice. We can achieve reasonable and accurate results by coupling chemical mass balance and factor analysis with nonnegative constraint models. That is,we use a nonnegative constraint analysis model to get the non-linear fingerprint of pollutants and then the mature chemical mass model to get the accurate contribution ratio of pollutants. A case study shows that the factor load matrix and the factor score matrix that are derived from the coupling technique will be more credible and create more accurate calculations for the pollutant contribution ratio.
出处 《环境科学学报》 CAS CSCD 北大核心 2011年第2期316-321,共6页 Acta Scientiae Circumstantiae
基金 国家水体污染控制与治理科技重大专项课题(No.2009ZX07419-003 2008ZX07207-007) 教育部新世纪优秀人才支持计划项目资助(No.NECT-09-0230)~~
关键词 非负约束因子分析 化学质量平衡模型 污染源解析 水体污染 nonnegative matrix factorization chemical mass balance source apportionment of pollutants water pollution
作者简介 陈海洋(1978-),男,E-mail:Chen.haiyang@hotmail.com; 通讯作者(责任作者),E-mail:teng1974@163.com责任作者简介:滕彦国(1974-),男,北京师范大学水科学研究院教授,博士生导师.主要研究方向是环境地球化学与水化学.其论文有30多篇被SCI、EI收录.
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  • 5刘宗峰,郎印海,曹正梅,马启敏.黄河口表层沉积物多环芳烃污染源解析研究[J].环境科学研究,2008,21(5):79-84. 被引量:33

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