Application of positive matrix factorization in characterization of PM10 and PM2.5 emission sources at urban roadside

Chemosphere ◽  
2012 ◽  
Vol 88 (1) ◽  
pp. 120-130 ◽  
Author(s):  
B. Srimuruganandam ◽  
S.M. Shiva Nagendra
Keyword(s):  
Matrix Factorization ◽  
Positive Matrix Factorization ◽  
Emission Sources ◽  
Positive Matrix ◽  
Pm10 And Pm2.5

scholarly journals Characterization of aerosol sources in León (Spain) using Positive Matrix Factorization and weather types

2021 ◽  
Vol 754 ◽  
pp. 142045 ◽  
Author(s):  
Fernanda Oduber ◽  
Ana Isabel Calvo ◽  
Amaya Castro ◽  
Carlos Blanco-Alegre ◽  
Célia Alves ◽  
...  
Keyword(s):  
Matrix Factorization ◽  
Positive Matrix Factorization ◽  
Positive Matrix ◽  
Weather Types ◽  
Aerosol Sources

scholarly journals Geochemical Mapping, Risk Assessment, and Source Identification of Heavy Metals in Road Dust Using Positive Matrix Factorization (PMF)

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 614
Author(s):  
Muhammad Faisal ◽  
Zening Wu ◽  
Huiliang Wang ◽  
Zafar Hussain ◽  
Chenyang Shen
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Matrix Factorization ◽  
Anthropogenic Activities ◽  
Contamination Factor ◽  
Road Dust ◽  
Positive Matrix Factorization ◽  
Prevention Measures ◽  
Positive Matrix ◽  
The City

Heavy metals in road dust pose a significant threat to human health. This study investigated the concentrations, patterns, and sources of eight hazardous heavy metals (Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg) in the street dust of Zhengzhou city of PR China. Fifty-eight samples of road dust were analyzed based on three methods of risk assessment, i.e., Geo-Accumulation Index (Igeo), Potential Ecological Risk Assessment (RI), and Nemerow Synthetic Pollution Index (PIN). The results exhibited higher concentrations of Hg and Cd 14 and 7 times higher than their background values, respectively. Igeo showed the risks of contamination in a range of unpolluted (Cr, Ni) to strongly polluted (Hg and Cd) categories. RI came up with the contamination ranges from low (Cr, Ni, Cu, Zn, As, and Pb) to extreme (Cd and Hg) risk of contamination. The risk of contamination based on PIN was from safe (Cu, As, and Pb) to seriously high (Cd and Hg). The results yielded by PIN indicated the extreme risk of Cd and Hg in the city. Positive Matrix Factorization was used to identify the sources of contamination. Factor 1 (vehicular exhaust), Factor 2 (coal combustion), Factor 3 (metal industry), and Factor 4 (anthropogenic activities), respectively, contributed 14.63%, 35.34%, 36.14%, and 13.87% of total heavy metal pollution. Metal’s presence in the dust is a direct health risk for humans and warrants immediate and effective pollution control and prevention measures in the city.

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