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Open AccessArticle

Source Apportionment of Polycyclic Aromatic Hydrocarbons in Sediment by the Application of Non-Negative Factor Analysis: A Case Study of Dalian Bay

by Fu-Lin Tian 1,2, Fa-Yun Li 1,2,*, De-Gao Wang 3 and Yan-Jie Wang 1,2
1
Institute of Eco-Environmental Sciences, Liaoning Shihua University, Fushun 113001, China
2
National & Local United Engineering Laboratory of Petroleum Chemical Process Operation, Optimization and Energy Conservation Technology, Liaoning Shihua University, Fushun 113001, China
3
School of Environmental Science and Engineering, Dalian Maritime University, Dalian 116026, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(4), 761; https://doi.org/10.3390/ijerph15040761
Received: 28 February 2018 / Revised: 30 March 2018 / Accepted: 7 April 2018 / Published: 16 April 2018
(This article belongs to the Special Issue Non-Point Source Pollution and Environmental Assessment)
An improved method, factor analysis with non-negative constraints (FA-NNC) was adopted to apportion the sources of sediment polycyclic aromatic hydrocarbons (PAHs) in Dalian Bay, China. Cosine similarity and Monte Carlo uncertainty analysis were used to assist the FA-NNC source resolution. The results identified three sources for PAHs, which were overall traffic, diesel engine emissions and residential coal combustion. The contributions of these sources were quantified as 78 ± 4.6% from overall traffic, 12 ± 3.2% from diesel engine emissions, and 10 ± 1.9% from residential coal combustion. The results from the Monte Carlo uncertainty analysis indicated that the model was robust and convergent. View Full-Text
Keywords: receptor model; statistical analysis; coastal area; organic pollutants receptor model; statistical analysis; coastal area; organic pollutants
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Tian, F.-L.; Li, F.-Y.; Wang, D.-G.; Wang, Y.-J. Source Apportionment of Polycyclic Aromatic Hydrocarbons in Sediment by the Application of Non-Negative Factor Analysis: A Case Study of Dalian Bay. Int. J. Environ. Res. Public Health 2018, 15, 761.

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