Abstract
ABSTRACT Eight composite PM10-2.5 source profiles were developed for resuspended dust and vehicle exhaust emissions with 32 chemical species, including 21 elements (Al, As, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Mo, Na, Ni, Pb, S, Sb, Se, V, and Zn), 9 water-soluble ions (Na+, K+, Mg2+, Ca2+, NH4+, Cl–, F–, NO3–, and SO42–), and carbonaceous fractions (OC and EC). Dust samples were dominated by crustal elements (Al, Ca, Fe, and Mg) while exhaust emissions showed high abundances of carbonaceous aerosol (OC and EC). Crustal species (Al, Fe, Mg, and Na) were more enriched over native soils in PM10-2.5 as compared to PM2.5. The higher coefficients of divergence (COD) indicate that profiles differ from each other. Ca accounted for nearly 30% of PM10-2.5 mass in construction dust while Fe accounted for nearly 20% of PM10-2.5 mass in paved road dust. Three- and four-wheeler diesel exhaust profiles consisted of 5–7% EC, with 6–10 times higher Pb, Se, and S abundances than those in two-wheeler gasoline exhaust profile. The heavy-duty diesel exhaust profile consist of nearly 20% EC with abundant (> 0.5%) trace elements (e.g., Pb, Se, and Zn).
Highlights
Air pollution is of great concern in India, especially the high levels of particulate matter (PM) emitted from uncontrolled industrial processes, solid waste and biomass burning, vehicular exhaust, and resuspended road dust (Pant and Harrison, 2013; Pant et al, 2015)
This study reports additional PM10-2.5 chemical source profiles for resuspended dust and vehicle exhaust emissions specific to India
This paper describes the PM10-2.5 chemical profiles for the eight resuspended dust and vehicle exhaust emissions tests
Summary
Air pollution is of great concern in India, especially the high levels of particulate matter (PM) emitted from uncontrolled industrial processes, solid waste and biomass burning, vehicular exhaust, and resuspended road dust (Pant and Harrison, 2013; Pant et al, 2015). Real-world source characterizations are needed to obtain chemical source profiles for input to receptor models, such as the Chemical Mass Balance (CMB), to identify and quantify source contributions. The U.S EPA SPECIATE (USEPA, 2013), European SPECIEUROPE (Pernigotti et al, 2016), and China Source Profile Shared Service (CSPSS) (Liu et al, 2017) databases have assembled many of these profiles. Gargava and Rajagopalan (2016) found that road dust
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