Source Apportionment of PM₁₀by Positive Matrix Factorization in Urban Area of Mumbai, India

Abstract

Particulate Matter (PM10) has been one of the main air pollutants exceeding the ambient standards in most of the major cities in India. During last few years, receptor models such as Chemical Mass Balance, Positive Matrix Factorization (PMF), PCA–APCS and UNMIX have been used to provide solutions to the source identification and contributions which are accepted for developing effective and efficient air quality management plans. Each site poses different complexities while resolving PM10 contributions. This paper reports the variability of four sites within Mumbai city using PMF. Industrial area of Mahul showed sources such as residual oil combustion and paved road dust (27%), traffic (20%), coal fired boiler (17%), nitrate (15%). Residential area of Khar showed sources such as residual oil combustion and construction (25%), motor vehicles (23%), marine aerosol and nitrate (19%), paved road dust (18%) compared to construction and natural dust (27%), motor vehicles and smelting work (25%), nitrate (16%) and biomass burning and paved road dust (15%) in Dharavi, a low income slum residential area. The major contributors of PM10 at Colaba were marine aerosol, wood burning and ammonium sulphate (24%), motor vehicles and smelting work (22%), Natural soil (19%), nitrate and oil burning (18%).

Biomonitoring of metals for air pollution assessment using a hemiepiphyte herb (Struthanthus flexicaulis)

“…PC1 showed a strong correlation among elements from natural origin, such as those from plant constituents (Ca, K, Mg, P and S) and from soil (Ba, Ca, Fe, K, Mg and Ti). These results are consistent with the plant's biochemistry, contrary to the EF values >2 that indicated anthropogenic influence (von Schneidemesser et al, 2010;Gupta et al, 2012).…”

“…The relationship among elements strongly suggests anthropogenic origin, considering that Cr, Cu, La, Pb, Sr and Zn (which do not appear in PC1) are moderately distributed among these PCs. These elements are mainly related to anthropogenic sources, as also indicated by EF > 2 (Quiterio et al, 2004;Guéguen et al, 2012;Godoy et al, 2009;Castilho et al, 2012;Gupta et al, 2012). Zinc is considered to be an indicator of waste burning (Gupta et al, 2012), industrial activity (Quiterio et al, 2004;Mateus et al, 2013), tire wear and brake linings (Khan et al, 2010).…”

Source Apportionment of PM10 at an Urban Site of a South Asian Mega City

“…While for the coarse particle four factos were recognized including marine aerosols, crustal/soil dust, nitrates and road side). Gupta et al (2012) reported the PM sources of various sites within Mumbai city using PMF. Industrial area of Mahul showed sources such as residual oil combustion and paved road dust, traffic, coal fired boiler and nitrate sources.…”

Source Apportionment for Water Soluble Organic Matter of Submicron Aerosol: A Comparison between Foggy and Nonfoggy Episodes

“…The ratio of Q true to Q robust is another parameter to evaluate the PMF modeled results. The Q robust is estimated excluding the outlier data which are samples having scaled residual greater than 4 and Q true is estimated including all the data points (Gupta et al, 2012;Waked et al, 2013). The ratio close to 1 indicates better solution and greater than 1.5 indicates influence of peak events on the model.…”