Using DN-PMF as a sensitivity test for conventional PMF analysis at three towns in South Africa, 2017 -2018.

During receptor source apportionment, factor analysis utilizes the covariance of compositional variables to separate sources of ambient pollutants.One of the main assumptions is that although the factors are distinct, the mixture is homogenous near the receptor point.Meteorology variations should cause concentration variations, in addition to emission rate changes in the atmosphere.Conventional positive matrix factorization (PMF) thus loses information.By incorporating the ventilation coefficient, dispersion normalized PMF (DN-PMF) reduces the dilution effects.Pretoria Six factors were identified by the PCA model (SPSS).The six sources assigned to the PMF model include resuspended dust (12.6%), biomass burning (24%), Secondary S (29%), vehicular emissions (11%), coarse particulate matter (15.7%) and industrial emissions (7.8).DN-PMF isolates biomass burning (3.7%) and vehicular emissions (41%).As in the C-PMF, there is a strong Cl-Pb correlation in the DN-PMF biomass factor.Thoyohandou Six factors were identified by the PCA model (SPSS).The six sources assigned to the PMF model include biomass burning (13.4%), vehicular emissions (2.1%), Vegetative burning (1.7%), coal burning (35.6%), industrial/mining (26%) and coarse dust (21.4%).DN-PMF isolates Resuspended Dust (16%), Industry (26.4%),Vehicular emissions (1.9%) and reduces biomass burning (5%).Cl is the dominant tracer in the vegetative burning factor for the conventional PMF and is dominant in the biomass factor in the DN-PMF.Cape Town (Kraaifontein) Seven factors were identified by the PCA model (SPSS).The seven sources assigned to the PMF model include Secondary S (15%), coarse particulates (9.7%), industry emissions (29%), zinc smelter emissions (6%), exhaust emissions (14%), sea air (9.3%), biomass burning (17%).DN-PMF included heavy industry (15%), exhaust (23%) increasing zinc smelter emissions (18%).In the conventional PMF model, Cl is a dominant tracer for sea spray, for the DN-PMF, the Cl is in combination with Cu and Zn -which implies vehicular emissions.

Publication Details

Published
2024-10-11
DOI
https://doi.org/10.38140/cem30.8
Primary Topic
Statistical Methods in Epidemiology
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article
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article

Using DN-PMF as a sensitivity test for conventional PMF analysis at three towns in South Africa, 2017 -2018.

Statistical Methods in Epidemiology
article

Using DN-PMF as a sensitivity test for conventional PMF analysis at three towns in South Africa, 2017 -2018.

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Abstract

During receptor source apportionment, factor analysis utilizes the covariance of compositional variables to separate sources of ambient pollutants.One of the main assumptions is that although the factors are distinct, the mixture is homogenous near the receptor point.Meteorology variations should cause concentration variations, in addition to emission rate changes in the atmosphere.Conventional positive matrix factorization (PMF) thus loses information.By incorporating the ventilation coefficient, dispersion normalized PMF (DN-PMF) reduces the dilution effects.Pretoria Six factors were identified by the PCA model (SPSS).The six sources assigned to the PMF model include resuspended dust (12.6%), biomass burning (24%), Secondary S (29%), vehicular emissions (11%), coarse particulate matter (15.7%) and industrial emissions (7.8).DN-PMF isolates biomass burning (3.7%) and vehicular emissions (41%).As in the C-PMF, there is a strong Cl-Pb correlation in the DN-PMF biomass factor.Thoyohandou Six factors were identified by the PCA model (SPSS).The six sources assigned to the PMF model include biomass burning (13.4%), vehicular emissions (2.1%), Vegetative burning (1.7%), coal burning (35.6%), industrial/mining (26%) and coarse dust (21.4%).DN-PMF isolates Resuspended Dust (16%), Industry (26.4%),Vehicular emissions (1.9%) and reduces biomass burning (5%).Cl is the dominant tracer in the vegetative burning factor for the conventional PMF and is dominant in the biomass factor in the DN-PMF.Cape Town (Kraaifontein) Seven factors were identified by the PCA model (SPSS).The seven sources assigned to the PMF model include Secondary S (15%), coarse particulates (9.7%), industry emissions (29%), zinc smelter emissions (6%), exhaust emissions (14%), sea air (9.3%), biomass burning (17%).DN-PMF included heavy industry (15%), exhaust (23%) increasing zinc smelter emissions (18%).In the conventional PMF model, Cl is a dominant tracer for sea spray, for the DN-PMF, the Cl is in combination with Cu and Zn -which implies vehicular emissions.

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Statistical Methods in Epidemiology
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Using DN-PMF as a sensitivity test for conventional PMF analysis at three towns in South Africa, 2017 -2018. · (2024) | TGRS Research Map | TGRS