Metallic species in PM 10 and source apportionment using PCA-MLR modeling over mid-Brahmaputra Valley
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ORIGINAL PAPER
Metallic species in PM10 and source apportionment using PCA-MLR modeling over mid-Brahmaputra Valley Pratibha Deka 1 & Pranamika Bhuyan 1 & Rebecca Daimari 1 & Kali Prasad Sarma 1 & Raza Rafiqul Hoque 1
Received: 23 June 2015 / Accepted: 8 February 2016 # Saudi Society for Geosciences 2016
Abstract This study was conducted to understand the attributes of metallic species associated with PM10 over MidBrahmaputra Valley. PM10 was sampled for a yearlong period (December 2008 to November 2009) at a rural receptor site by a high volume sampler, which was chemically analyzed for 10 metallic species viz. Mg, K, Ca, Cr, Mn, Fe, Co, Ni, Cu, Cd, and Pb by acid digestion followed by estimation by ICP-OES. The mean PM 10 for the study period was found to be 147.10 ± 153 μg m−3, and marked seasonality of the mass concentrations of PM10 was observed. However, the concentrations of the metallic species did not show seasonality that was statistically significant. High PM10 levels during monsoon were therefore attributed to delay and deficit rainfall, secondary formation of aerosols, and favorable atmospheric conditions viz. subsidence and thermal inversion. This was as evident from analyses of vertical temperature profile and HYSPLIT air mass trajectories. The enrichment factors revealed that K, Cr, Ni, and Pb were moderately, and Cd highly enriched in PM10 indicating anthropogenic contribution. Interspecies correlations and principal component analysismultiple linear regression (PCA-MLR) of elements associated in PM10 indicates biomass burning, crustal dust, soil, and fossil fuel burning as the possible sources. The source contributions were validated and the contributions of total elements by the sources to the predicted concentrations by PCA-MLR showed good agreement.
* Raza Rafiqul Hoque [email protected]
1
Department of Environmental Science, Tezpur University, Tezpur 784028, India
Keywords PM10 . Metallic species . Source apportionment . PCA-MLR . HYSPLIT trajectory
Introduction Atmospheric particulates have drawn remarkable attention today for their effects on human health, ecosystems, atmospheric chemistry, and the climate system. Recently, International Agency for Research on Cancer (IARC 2013) had declared outdoor air pollution as carcinogenic to human beings. Particulate matter of aerodynamic diameter ≤10 μm (PM10) is able to penetrate the bronchi, PM2.5 the lung, and nano particles are able to pass through the lungs and enter the circulatory system (Dockery and Stone 2007; Pe’rez et al. 2008). According to a World Health Organization (WHO) update, ambient air pollution was estimated to cause 3.7 million premature deaths worldwide in 2012 and 88 % of the deaths occurred in low- and middle-income countries and the greatest number in the Western Pacific and South-East Asia regions (WHO 2014). The Organization for Economic Co-operation and Development (OECD) in its Environmental Outlook 2050 report warns that urban air pollution could become the biggest environmental cause of premature death by 2050
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