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Particulate Size Distribution and Sources Evaluation of n-Alkanes during Long-Term Haze Episode around Chaohu Lake, Eastern China

n-Alkanes (from nC_(16) to nC_(32)) associated with particulate matters were determined in the ambient air around Chaohu Lake, Eastern China, from October to December in 2014 during a long-term haze episode. The total concentrations of particle bounded n-alkanes varied from 332 to 2500 ng m^(-3), wi...

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Bibliographic Details
Published in:Aerosol and Air Quality Research 2017, Vol.17 (8), p.1975-1984
Main Authors: Xu, Qiu-Ping, Wang, Ji-Zhong, Liu, Jia-Qin, Peng, Shu-Chuan
Format: Article
Language:English
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Summary:n-Alkanes (from nC_(16) to nC_(32)) associated with particulate matters were determined in the ambient air around Chaohu Lake, Eastern China, from October to December in 2014 during a long-term haze episode. The total concentrations of particle bounded n-alkanes varied from 332 to 2500 ng m^(-3), with the homologues of nC_(24)-nC_(30) the most abundant species. Spatial analysis revealed that low concentrations of n-alkanes existed at the sites close to Chaohu Lake, while high concentrations were generally at locations distant from the lake. For all aggregated fractions, most n-alkanes were distributed in fine particles with the mean geometric mean diameter (GMD) varying from 3.0 ± 0.6 μm for nC_(16) to 2.1 ± 0.6 μm for nC_(32). Short chain n-alkanes were accumulated in coarse particles with a unimodal distribution, but long chain aliphatic hydrocarbons appeared to have a biomodal distribution in fine and coarse particles. The mass size distribution of individual n-alkane homologue was predominantly influenced by its volatility; thus GMDs were well correlated with the logarithmically transformed subcooled liquid vapor pressures (P_L °, Pa) of n-alkanes at each samP_Ling site, following the equation: GMDs = m_gLogP_L° + bg. Furthermore, m_g and b_g obtained from all locations tended to exhibit a significant linear correlation. This suggests that all saturated aliphatic hydrocarbons follow a similar accumulation mode during a haze episode, which allows us to predict the size distribution and GMD of a compound based on its P_L °.
ISSN:1680-8584
2071-1409
DOI:10.4209/aaqr.2017.05.0189