Cluster analysis of electron microprobe analysis data of individual particles for source apportionment of air particulate matter

Werner A. Van Borm; Freddy C. Adams

doi:10.1016/0004-6981(88)90141-2

Cluster analysis of electron microprobe analysis data of individual particles for source apportionment of air particulate matter

Atmospheric Environment (1967) ◽

10.1016/0004-6981(88)90141-2 ◽

1988 ◽

Vol 22 (10) ◽

pp. 2297-2307 ◽

Cited By ~ 26

Author(s):

Werner A. Van Borm ◽

Freddy C. Adams

Keyword(s):

Cluster Analysis ◽

Particulate Matter ◽

Source Apportionment ◽

Electron Microprobe ◽

Microprobe Analysis ◽

Electron Microprobe Analysis ◽

Analysis Data ◽

Air Particulate Matter ◽

Air Particulate ◽

Individual Particles

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Source Apportionment for the Zinc—Containing Component of Air Particulate Matter using Automated Electron Probe Micro Analysis of Individual Particles

International Journal of Environmental & Analytical Chemistry ◽

10.1080/03067318708077139 ◽

1987 ◽

Vol 31 (2-4) ◽

pp. 165-182 ◽

Cited By ~ 7

Author(s):

W. Van Borm ◽

P. Van Espen ◽

F. Adams ◽

M. Demuynck

Keyword(s):

Particulate Matter ◽

Source Apportionment ◽

Electron Probe ◽

Electron Probe Micro Analysis ◽

Air Particulate Matter ◽

Air Particulate ◽

Micro Analysis ◽

Individual Particles

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Source Apportionment of Heavy Metals in Air Particulate Matter Using Automated Electron Probe Micro Analysis

Environmental Hygiene ◽

10.1007/978-3-642-73766-4_41 ◽

1988 ◽

pp. 193-196

Author(s):

W. Van Borm ◽

F. Adams

Keyword(s):

Heavy Metals ◽

Particulate Matter ◽

Source Apportionment ◽

Electron Probe ◽

Electron Probe Micro Analysis ◽

Air Particulate Matter ◽

Air Particulate ◽

Micro Analysis

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Calculating biotite formula from electron microprobe analysis data using a machine learning method based on principal components regression

Lithos ◽

10.1016/j.lithos.2020.105371 ◽

2020 ◽

Vol 356-357 ◽

pp. 105371 ◽

Cited By ~ 1

Author(s):

Xiaoyan Li ◽

Chao Zhang ◽

Harald Behrens ◽

Francois Holtz

Keyword(s):

Machine Learning ◽

Principal Components ◽

Electron Microprobe ◽

Microprobe Analysis ◽

Electron Microprobe Analysis ◽

Analysis Data ◽

Machine Learning Method ◽

Learning Method ◽

Principal Components Regression

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Calculating amphibole formula from electron microprobe analysis data using a machine learning method based on principal components regression

Lithos ◽

10.1016/j.lithos.2020.105469 ◽

2020 ◽

Vol 362-363 ◽

pp. 105469 ◽

Cited By ~ 4

Author(s):

Xiaoyan Li ◽

Chao Zhang ◽

Harald Behrens ◽

Francois Holtz

Keyword(s):

Machine Learning ◽

Principal Components ◽

Electron Microprobe ◽

Microprobe Analysis ◽

Electron Microprobe Analysis ◽

Analysis Data ◽

Machine Learning Method ◽

Learning Method ◽

Principal Components Regression

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Elemental Characterization and Source Apportionment of Air Particulate Matter in Two Contrastive Industrial Areas in Nigeria

Journal of Applied Sciences ◽

10.3923/jas.2005.1797.1801 ◽

2005 ◽

Vol 5 (10) ◽

pp. 1797-1801 ◽

Cited By ~ 4

Author(s):

Okuo . ◽

James M. . ◽

C.I. Ndiokwere .

Keyword(s):

Particulate Matter ◽

Source Apportionment ◽

Air Particulate Matter ◽

Industrial Areas ◽

Air Particulate ◽

Elemental Characterization

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Characterization and source apportionment of ambient air particulate matter (PM2.5) in Karachi

The Science of The Total Environment ◽

10.1016/j.scitotenv.2011.10.056 ◽

2012 ◽

Vol 425 ◽

pp. 176-183 ◽

Cited By ~ 72

Author(s):

M. Mansha ◽

Badar Ghauri ◽

Said Rahman ◽

Arif Amman

Keyword(s):

Particulate Matter ◽

Source Apportionment ◽

Ambient Air ◽

Air Particulate Matter ◽

Air Particulate

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Source Apportionment of Air Particulate Matter by Chemical Mass Balance (CMB) and Comparison with Positive Matrix Factorization (PMF) Model

Aerosol and Air Quality Research ◽

10.4209/aaqr.2006.10.0021 ◽

2007 ◽

Vol 7 (4) ◽

pp. 446-468 ◽

Cited By ~ 26

Author(s):

Bilkis A. Begum ◽

Swapan K. Biswas ◽

Philip K. Hopke

Keyword(s):

Particulate Matter ◽

Mass Balance ◽

Source Apportionment ◽

Matrix Factorization ◽

Positive Matrix Factorization ◽

Chemical Mass Balance ◽

Positive Matrix ◽

Air Particulate Matter ◽

Pmf Model ◽

Air Particulate

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Corrigendum to “Calculating biotite formula from electron microprobe analysis data using a machine learning method based on principal components regression” [Lithos 356-357 (2020) 105371]

Lithos ◽

10.1016/j.lithos.2020.105506 ◽

2020 ◽

Vol 362-363 ◽

pp. 105506

Author(s):

Xiaoyan Li ◽

Chao Zhang ◽

Harald Behrens ◽

Francois Holtz

Keyword(s):

Machine Learning ◽

Principal Components ◽

Electron Microprobe ◽

Microprobe Analysis ◽

Electron Microprobe Analysis ◽

Analysis Data ◽

Machine Learning Method ◽

Learning Method ◽

Principal Components Regression

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Source apportionment of air particulate matter in Antwerp, Belgium

Journal of Aerosol Science ◽

10.1016/0021-8502(87)90074-7 ◽

1987 ◽

Vol 18 (6) ◽

pp. 593-596 ◽

Cited By ~ 7

Author(s):

W.A. Van Borm ◽

F.C. Adams

Keyword(s):

Particulate Matter ◽

Source Apportionment ◽

Air Particulate Matter ◽

Air Particulate

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Identification and source apportionment of polycyclic aromatic hydrocarbons in ambient air particulate matter of Riyadh, Saudi Arabia

Environmental Science and Pollution Research ◽

10.1007/s11356-013-1946-9 ◽

2013 ◽

Vol 21 (1) ◽

pp. 558-567 ◽

Cited By ~ 20

Author(s):

Aarif H. El-Mubarak ◽

Ahmed I. Rushdi ◽

Khalid F. Al-Mutlaq ◽

Abdulqader Y. Bazeyad ◽

Staci L. M. Simonich ◽

...

Keyword(s):

Saudi Arabia ◽

Polycyclic Aromatic Hydrocarbons ◽

Particulate Matter ◽

Source Apportionment ◽

Aromatic Hydrocarbons ◽

Ambient Air ◽

Air Particulate Matter ◽

Air Particulate ◽

Polycyclic Aromatic

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