Source apportionment of pollution in groundwater source area using factor analysis and positive matrix factorization methods

被引:34
|
作者
Guo, Xueru [1 ,2 ]
Zuo, Rui [1 ,2 ]
Shan, Dan [3 ]
Cao, Yang [1 ,2 ]
Wang, Jinsheng [1 ,2 ]
Teng, Yanguo [1 ,2 ]
Fu, Qing [4 ]
Zheng, Binghui [4 ]
机构
[1] Beijing Normal Univ, Coll Water Sci, Beijing 100875, Peoples R China
[2] Beijing Normal Univ, Engn Res Ctr Groundwater Pollut Control & Remedia, Minist Educ China, Beijing, Peoples R China
[3] Sino Japan Friendship Ctr Environm Protect, Beijing, Peoples R China
[4] Chinese Res Inst Environm Sci, Beijing, Peoples R China
来源
HUMAN AND ECOLOGICAL RISK ASSESSMENT | 2017年 / 23卷 / 06期
基金
中国国家自然科学基金;
关键词
source apportionment; groundwater; factor analysis; positive matrix factorization; water source area; SOURCE IDENTIFICATION; ORGANIC CONTAMINANTS; ALLUVIAL AQUIFER; WATER-QUALITY; HEAVY-METALS; PMF ANALYSIS; SOURCE FIELD; NITRATE; SEDIMENTS; URBAN;
D O I
10.1080/10807039.2017.1322894
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
By means of factor analysis (FA) and positive matrix factorization (PMF) methods, groundwater pollution sources were identified in the Jinji groundwater source area, which is beside the Yellow River and is the only urban water supply source for the city of Wuzhong in Northwestern China. The sources of groundwater were quantified based on 16 samples of shallow groundwater from the source area. The source apportionment with the PMF model identified three dominant groundwater pollution sources. These were anthropogenic activities of agricultural and industrial pollution with a pollution contribution of 53.0%, water-rock interaction of 24.6%, and evaporation and concentration of 22.4%. The source apportionment with the FA model identified four sources which were evaporation and concentration, with the largest contribution (42.6%), followed by anthropogenic activities (29.2%), mineral dissolution and industrial pollution (22.4%), and natural effects (5.8%). Specific attention should be paid to these natural (fluoride, TH, etc.) and anthropogenic sources (NH4+, NO2-, turbidity, total bacterial count, etc.), and pertinent measures should be taken to control local groundwater pollution. The most significant trait of the PMF is its scientific interpretation and physical explanation of the results, depending on non-negative restriction of the pollution source profiles and contributions.
引用
收藏
页码:1417 / 1436
页数:20
相关论文
共 50 条
  • [41] Comparison of Positive Matrix Factorization and Multilinear Engine for the source apportionment of particulate pollutants
    Ramadan, Z
    Eickhout, B
    Song, XH
    Buydens, LMC
    Hopke, PK
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2003, 66 (01) : 15 - 28
  • [42] Iterated confirmatory factor analysis for pollution source apportionment
    Christensen, William F.
    Schauer, James J.
    Lingwall, Jeff W.
    ENVIRONMETRICS, 2006, 17 (06) : 663 - 681
  • [43] Source apportionment of PM10 by positive matrix factorization model at a source region of biomass burning
    Saggu, Gurpreet Singh
    Mittal, Susheel Kumar
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2020, 266
  • [44] Source apportionment of PAHs in surface sediments using positive matrix factorization combined with GIS for the estuarine area of the Yangtze River, China
    Yu, Wenwen
    Liu, Ruimin
    Wang, Jiawei
    Xu, Fei
    Shen, Zhenyao
    CHEMOSPHERE, 2015, 134 : 263 - 271
  • [45] Pollution assessment and source apportionment of shallow groundwater in Suzhou mining area, China
    Zhao W.
    Zhao L.
    Gong J.
    Zhou W.
    Qian J.
    Earth Science Frontiers, 2021, 28 (05) : 1 - 14
  • [46] Source Apportionment and Geographic Distribution of Heavy Metals and as in Soils and Vegetables Using Kriging Interpolation and Positive Matrix Factorization Analysis
    Su, Huiyue
    Hu, Yueming
    Wang, Lu
    Yu, Huan
    Li, Bo
    Liu, Jiangchuan
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (01)
  • [47] Source apportionment of ambient fine particle size distribution using positive matrix factorization in Erfurt, Germany
    Yue, Wei
    Stoelzel, Matthias
    Cyrys, Josef
    Pitz, Mike
    Heinrich, Joachim
    Kreyling, Wolfgang G.
    Wichmann, H. -Erich
    Peters, Annette
    Wang, Sheng
    Hopke, Philip K.
    SCIENCE OF THE TOTAL ENVIRONMENT, 2008, 398 (1-3) : 133 - 144
  • [48] Chemical characterization of PM1.0 aerosol in Delhi and source apportionment using positive matrix factorization
    Amrita Jaiprakash
    Gazala Singhai
    Ramya Sunder Habib
    Tarun Raman
    Environmental Science and Pollution Research, 2017, 24 : 445 - 462
  • [49] Chemical characterization of PM1.0 aerosol in Delhi and source apportionment using positive matrix factorization
    Jaiprakash
    Singhai, Amrita
    Habib, Gazala
    Raman, Ramya Sunder
    Gupta, Tarun
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2017, 24 (01) : 445 - 462
  • [50] Organic aerosol source apportionment by using rolling positive matrix factorization: Application to a Mediterranean coastal city
    Chazeau, Benjamin
    El Haddad, Imad
    Canonaco, Francesco
    Temime-Roussel, Brice
    D'Anna, Barbara
    Gille, Gregory
    Mesbah, Boualem
    Prevot, Andre S. H.
    Wortham, Henri
    ATMOSPHERIC ENVIRONMENT-X, 2022, 14