The use of multivariate analysis to identify sources of selected elements in the Boston urban aerosol

Biswas

Hopke

et al. 2006

Aerosol Air Qual. Res.

Self Cite

PIXE (Proton Induced X-Ray Emission) and PIGE (Proton Induced Gamma Ray Emission) have been used to measure the concentration of over 20 elements present in coarse and fine atmospheric particle samples. These samples were collected at a semi-residential site at Dhaka, Bangladesh from July 2002 to June 2003. The multi-elemental capability of PIXE and PIGE enabled the use of these elemental-concentration data to define fingerprints of various coarse and fine particle sources in the atmosphere using factor analysis along with linear regression. Biplots between a major component of a given source identified by the factor analysis with another signature element were prepared. Regression analyses could then be performed on a subset of the plot to quantify the relationship between these constituents in this fingerprint. The identified fingerprints included anthropogenic sources, such as motor vehicles, Zn source, two-stroke engine, and fugitive Pb; as well as natural sources, such as sea spray and soil dust. In this study, the chemical compositions of elements of these fingerprints were compared with the results obtained from PMF modeling that had been obtained in a previous study.

Section: Principal Component Analysismentioning

confidence: 99%

“…Factor analysis is a multivariate statistical technique used in environmental studies to identify sources from data taken at receptor sites (Hopke et al, 1976;Henry, 1997;Huang et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Multi-element Analysis and Characterization of Atmospheric Particulate Pollution in Dhaka

Biswas

Hopke

et al. 2006

Aerosol Air Qual. Res.

Self Cite

“…Principal component analysis (PCA) (Hopke 1985) used measurements of pollutant concentrations at a sampling site to identify significantly correlated variables. This method extracts components explaining the majority of variance of the data matrix which was then qualitatively interpreted as possible sources (Hopke 1985, Hopke et al 1976, Wolff et al 1985. PCA is often useful to provide information regarding source characteristics in terms of the elements that are associated with a given source type.…”

Section: Farm Gatementioning

confidence: 99%

Source Identification of Carbonaceous Aerosols During Winter Months in the Dhaka City

Roy

Islam

et al. 2012

J Bangladesh Acad Sci

Air particulate matter samples were collected using Air Metrics samplers from 11 -17 January and 19 -27 January, 2012 at Amin Bazar and Farm Gate sites, respectively. The sampling time was from 8 a.m. -4 p.m. Three samplers were used of which two samplers were for PM 2.5 samples, using Teflon and quartz filters and the others for PM 10 samples using Teflon filter. Organic and elemental carbons (OC and EC) were measured in PM 2.5 samples at both sites. It has been found that the EC concentration at Amin Bazar is higher than in Farm Gate. The contribution of EC may come from diesel, gasoline and coal/wood combustions in the Amin Bazar site. The present OC/EC data were compared with the previous data. It was found that the concentration of EC became higher than those in the previous year. During last couple of years, Government implemented different policies specially in case of motor vehicles to improve the air quality. But due to the use of diesel in quick rental power plants, the air quality start to deteriorate. BC plays an important role to change the climate. Hence, government should think of alternatives to meet the power demand in place of diesel.

“…Principal component analysis (PCA) (Hopke 1985) uses measurements of pollutant concentrations at a sampling site to identify significantly correlated variables. This method extracts components explaining the majority of variance of the data matrix that is then qualitatively interpreted as possible sources (Hopke 1985, Hopke et al 1976, Wolff et al 1985. PCA is often useful to provide information regarding source characteristics in terms of the elements that are associated with a given source type.…”

Section: Rcm = (Nh 4 ) 2 So 4 + Salt + Soil + Smoke + Omh + Bc + Zn + Pbmentioning

confidence: 99%

Characterization of Chittagong Aerosol by PCA Modeling

Biswas

Nasiruddin

2012

J Bangladesh Acad Sci

Black carbon and other selected trace elements concentrations in aerosol samples collected at the Continuous Air Monitoring Station (CAMS) in Chittagong, the second largest city in Bangladesh, were investigated for possible source contributions. The particulate matter (PM) sampling was done from end of winter to middle of rainy season (February and July, 2007) using dichotomous sampler. The samples collected in two fractions of <2.5 m (fine) and 2.5 to 10 m (coarse) were analyzed for elemental concentrations by proton induced X-ray emission (PIXE), hydrogen by proton elastic scattering analysis (PESA), and black carbon by reflectance measurement. The elemental data sets together with black carbon were analyzed by principal component analysis method to identify the possible sources contributing to the mass concentration of coarse and fine particulate matter (FPM) fractions. The best solutions were found to be six and seven factors for coarse and fine fractions respectively, which could explain more than 90% of the variance in the data set. The sources were identified as biomass burning/brick kiln, soil dust, road dust, Zn source, Pb source, motor vehicle, CNG (compressed natural gas) vehicle and sea salt. It was found that in coarse fraction, the sea salt is mixed with Zn source and in fine fraction, the road dust factor is mixed with CNG vehicle source.