A source apportionment receptor modelling technique based on principal component analysis (PCA) w... more A source apportionment receptor modelling technique based on principal component analysis (PCA) was applied on two segregated atmospheric particulate size fractions PM2.5 and PM2.5-10 sampled at one site of Kuala Lumpur. A total of 112 collocated samples of PM2.5 and PM2.5-10 collected by the Gent Stacked Filter Unit (SFU) were analyzed for the elemental constituents and subjected to the PCA. Five major factors were identified by the PCA with Varimax rotation for the coarse size fraction PM2.5-10, attributed to soil and re-suspended road dust (31.4%), construction works and cement plant (17.4%), industrial (12.1%), vehicular exhaust emission (10.7%), and non-ferrous smelter (9%). While for the fine particulates size fraction PM2.5, the major sources were identified as biomass burning and soil, the pigment based industry, industrial coal burning, vehicular emission and the non-ferrous smelter
Gravimetric and elemental analyses were conducted at a site in Kuala Lumpur from 2008 to 2010, re... more Gravimetric and elemental analyses were conducted at a site in Kuala Lumpur from 2008 to 2010, representing the local air quality of urban and traffic. Eighteen elements were detected by ED-XRF and was further analysed for enrichment factor and correlation study. About 19.7% elements were identified and detected in PM10, including 8.2% and 11.5% in fine and coarse fractions, respectively. Al was found predominant in coarse fraction. However its composition in PM2.5 was highly enriched pointed to some anthropogenic emission source. In fine particulates, the total mass was mostly dominated by Al, K, Mg and S. Those elements, probably from biomass burning accounted for more than 90% of total elemental detected in PM2.5.
A source apportionment receptor modelling technique based on principal component analysis (PCA) w... more A source apportionment receptor modelling technique based on principal component analysis (PCA) was applied on two segregated atmospheric particulate size fractions PM2.5 and PM2.5-10 sampled at one site of Kuala Lumpur. A total of 112 collocated samples of PM2.5 and PM2.5-10 collected by the Gent Stacked Filter Unit (SFU) were analyzed for the elemental constituents and subjected to the PCA. Five major factors were identified by the PCA with Varimax rotation for the coarse size fraction PM2.5-10, attributed to soil and re-suspended road dust (31.4%), construction works and cement plant (17.4%), industrial (12.1%), vehicular exhaust emission (10.7%), and non-ferrous smelter (9%). While for the fine particulates size fraction PM2.5, the major sources were identified as biomass burning and soil, the pigment based industry, industrial coal burning, vehicular emission and the non-ferrous smelter
Gravimetric and elemental analyses were conducted at a site in Kuala Lumpur from 2008 to 2010, re... more Gravimetric and elemental analyses were conducted at a site in Kuala Lumpur from 2008 to 2010, representing the local air quality of urban and traffic. Eighteen elements were detected by ED-XRF and was further analysed for enrichment factor and correlation study. About 19.7% elements were identified and detected in PM10, including 8.2% and 11.5% in fine and coarse fractions, respectively. Al was found predominant in coarse fraction. However its composition in PM2.5 was highly enriched pointed to some anthropogenic emission source. In fine particulates, the total mass was mostly dominated by Al, K, Mg and S. Those elements, probably from biomass burning accounted for more than 90% of total elemental detected in PM2.5.
Uploads
Papers by Sara Yasina Yusuf
collocated samples of PM2.5 and PM2.5-10 collected by the Gent Stacked Filter Unit (SFU) were analyzed for the elemental constituents and subjected to the PCA. Five
major factors were identified by the PCA with Varimax rotation for the coarse size fraction PM2.5-10, attributed to soil and re-suspended road dust (31.4%), construction
works and cement plant (17.4%), industrial (12.1%), vehicular exhaust emission (10.7%), and non-ferrous smelter (9%). While for the fine particulates size fraction PM2.5, the major sources were identified as biomass burning and soil, the pigment based industry, industrial coal burning, vehicular emission and the non-ferrous smelter
collocated samples of PM2.5 and PM2.5-10 collected by the Gent Stacked Filter Unit (SFU) were analyzed for the elemental constituents and subjected to the PCA. Five
major factors were identified by the PCA with Varimax rotation for the coarse size fraction PM2.5-10, attributed to soil and re-suspended road dust (31.4%), construction
works and cement plant (17.4%), industrial (12.1%), vehicular exhaust emission (10.7%), and non-ferrous smelter (9%). While for the fine particulates size fraction PM2.5, the major sources were identified as biomass burning and soil, the pigment based industry, industrial coal burning, vehicular emission and the non-ferrous smelter