PIXE analysis of PM_2.5 and PM_2.5–10 for air quality assessment of Islamabad, Pakistan: Application of chemometrics for source identification

Abstract

A Gent sampler was used to collect 379 pairs of filters from Nilore, a suburban area of Islamabad city. The study was designed to assess the concentration variations of trace elements in fine and coarse particulate matter due to anthropogenic activities and naturally occurring events. Source identification was performed by applying MATLAB software for principal component analysis (PCA), and cluster analysis (CA). The average fine and coarse particulate masses during the study period were 15.1 ± 11.9 and 37.3 ± 28.0 μg/m³ respectively which complies with the 24-h air quality limits set by the government of Pakistan. The application of PCA to PM_2.5 data suggests the PM contribution from sources such as soil, automobile exhaust and coal combustion, road dust and wearing of tyres, wood combustion, biomass burning and fertilizers and fungicides whereas for the PM_2.5–10 data shows signatures of suspended soil, automobile exhaust, road dust and wearing of tyres, wood and biomass burning, refuse incineration, Ni smelter, fertilizers and fungicides are obtained. Cluster analysis of PM_2.5 and PM_2.5–10 datasets reveals that there are mainly three contributory pollution sources and these are suspended soil particles, automobile related sources and wood and coal combustion.

Keywords:

• Chemometrics
• cluster analysis (CA)
• coarse particulates
• fine particulates
• proton induced X-ray emission (PIXE)
• proton induced γ-ray emission (PIGE)
• principal component analysis (PCA)

Acknowledgments

This study was performed under the aegis of IAEA/RCA Project RAS/7/013 entitled “Improved Information about Urban Air Quality Management” for the Asia and the Pacific region and the Higher Education Commission of Pakistan (HEC). The Institute of Geological and Nuclear Sciences (GNS), Lower Hutt, New Zealand is also acknowledged for their continuous support in PIXE analysis.