Assessment of source contributions to organic carbon in ambient fine particle using receptor model with inorganic and organic source tracers at an urban site of Beijing

Abstract

The collections of ambient fine particles were carried out in the period of January 16 to 31, 2013, in Beijing. The levels of carbonaceous aerosols (i.e., organic carbon and elemental carbon) in fine particles were determined. The chemical compositions of primary source tracers including alkanes, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(e)pyrene, benzo(ghi)perylene, picene, 17a(H)-22,29,30-trisnorhopane, levoglucosan, Al and Fe in fine particles were analyzed. Chemical mass balance (CMB) model coupled with inorganic and organic source tracers was utilized to estimate daily contributions of primary sources (e.g., coal combustion, biomass burning, dust source, mobile source) to organic carbon (OC). The sensitivity analysis of specific primary source was carried out in order to obtain the accurate contribution from primary sources. Our study indicated that CMB with inorganic and organic source tracer method was efficient for apportioning primary sources of OC in Beijing during high air pollution episodes.

Identification of Soil Heavy Metal Sources in a Large-Scale Area Affected by Industry

“…Commonly used receptor models include chemical mass balance (CMB), principal component analysis/multilinear regression (PCA-MLR), positive matrix factorization (PMF) and UNMIX models [10][11][12]. However, the judgement of the results of receptor models is highly subjective, mostly relying on previous experience and expert assessment, and the analytical results are difficult to verify [13][14][15][16]. The current research on receptor models is, on the one hand, related to the applicability of the model, such as the appropriate scale, the amount of sampled data and the appropriate research object, and on the other hand based on the analytical process of the optimization model, usually in combination with other methods.…”