A Preliminary Assessment of Chemical Constituents of Atmospheric Particulate Matter and their Sources in Faisalabad, Pakistan

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Date: Aug. 31, 2015
Publisher: Knowledge Bylanes
Document Type: Report
Length: 6,123 words
Lexile Measure: 1540L

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Byline: Wasim Javed, Ghulam Murtaza, Hamaad Raza Ahmad and Shahzad Maqsood Ahmed Basra

Summary:

Atmospheric total suspended particulate matter (TSP) mass and chemical constituents were characterized, collected on glass fiber filters using high volume air sampler in Faisalabad, Pakistan from May 2012 to April 2013. Two receptor models Principal Component Analysis (PCA) and UNMIX were used for the source identification in the study area. High volume TSP samples (n=288) were subjected to gravimetric and quantitative chemical analyses for determining trace elements (Pb, Cd, Ni, Zn, Cu, Fe) using atomic absorption spectroscopy and water-soluble cations +) and anions (Cl-, SO 2- and NO -) by ion chromatography. The average (Ca2+, Mg2+, Na+, K+, NH4 4 3 TSP concentration was 575 g m-3 that is 1.6 and 8 times higher than Pak NEQS (360 g m-3) and US EPA (75 g m-3) annual limits, respectively. The crustal elements Ca, Fe, Mg and Na were the largest contributors to TSP mass while elements of anthropogenic origin Pb, Cd, Ni, Cu and Zn had relatively lower concentrations.

The enrichment factors (EFs) for elemen ts indicated that Pb, Cd, Cu, Zn and Ni (with EFsgreater than 100) were highly enriched and are of anthropogenic origin. Both PCA and UNMIX models produced comparable factor compositions and identified four possible sources: (1) crude oil combustion, (2) re-suspended crustal/road dust, (3) combination of coal and biomass burning and (4) secondary particles. Results of EF, cluster analysis and correlation analysis also duly supported the model results of source identification.

Keywords: TSP; Elements; Source identification; PCA; UNMIX

Introduction

Over the last few decades, the atmospheric degradation has become a severe threat to human health and welfare in developing countries like Pakistan, where urbanization, motorization and industrialization coupled with energy demand are rapid. In particular, urban centers are facing the menace of air pollution primarily due to the presence of particulate matter (PM) and its associated chemical species in the atmosphere [1, 2]. This hazard is especially severe in the areas where emissions control technologies and strategies are limited due to lax legislative standards and enforcement of regulations [2-4]. Epidemiological studies have widely established a strong association between airborne PM having toxic constituents and respiratory- and cardiovascular- related increases in morbidity and mortality specifically in urban areas [5].

Chemical characterization atmospheric PM and their source identification are a prerequisite step for successfully instituting mitigation measures and air quality management that minimize consequent health impacts [4]. There are very limited data currently available on the chemical composition and source identification of PM in the urban areas of Pakistan [1, 4]. Some sporadic reports revealed that airborne PM is a serious environmental and health concern in urban areas of Pakistan [1-3, 6].

Source identification by receptor modeling has always been a useful tool for establishing air quality regulations. Over the past two decades, models such as Chemical Mass Balance, Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF), have been used in this regard [7]. During past few years, the UNMIX model has...

Source Citation

Source Citation   

Gale Document Number: GALE|A427966893