Application of PMF receptor model merging with PAHs signatures for source apportionment of black carbon in the continental shelf surface sediments of the Bohai and Yellow Seas, China

  • Yin Fang
  • , Yingjun Chen*
  • , Chongguo Tian
  • , Tian Lin
  • , Limin Hu
  • , Jun Li
  • , Gan Zhang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

Black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) are byproducts generated from the incomplete combustion of organic materials, including fossil fuels and biomass. The similar production processes shared by BC and PAHs provide the possibility to infer the BC sources using the PAHs signatures. This study successfully utilized data sets of BC and PAHs analyzed from the continental shelf surface sediments of the Bohai and Yellow Seas to a standard receptor model of positive matrix factorization (PMF) to apportion the sources of BC in the sediment matrix. Results showed that combustion of fossil fuels (i.e., coal and oil/petroleum) accounted for an average level of 83 ± 5% of the total BC preserved, which was significantly higher than that from the biomass burning (17 ± 5%). The spatial distributions of the fossil BC concentrations and percentages differed significantly from those of the biomass BC, implying their different geochemical behaviors in the continental shelf regimes and further emphasizing the importance to effectively differentiate between fossil BC and biomass BC. In addition to the relative proportions of the BC subtypes (char-BC/soot-BC), the regional-specific hydrodynamic conditions, including the cold cyclonic eddy, resuspension and coastal current, also exerted a significant influence on these spatial variations.

Original languageEnglish
Pages (from-to)1346-1359
Number of pages14
JournalJournal of Geophysical Research: Oceans
Volume121
Issue number2
DOIs
StatePublished - 1 Feb 2016
Externally publishedYes

Keywords

  • black carbon
  • continental shelf surface sediments
  • fossil fuels and biomass
  • hydrodynamic conditions
  • polycyclic aromatic hydrocarbons
  • positive matrix factorization receptor model

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