4.7 Article

Global atmospheric emission inventory of polycyclic aromatic hydrocarbons (PAHs) for 2004

Journal

ATMOSPHERIC ENVIRONMENT
Volume 43, Issue 4, Pages 812-819

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2008.10.050

Keywords

PAHs; Emission inventory; Global

Funding

  1. National Scientific Foundation of China [40730737, 140710019001]
  2. National Basic Research Program [2007CB407303]

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The global atmospheric emissions of the 16 polycyclic aromatic hydrocarbons (PAHs) listed as the US EPA priority pollutants were estimated using reported emission activity and emission factor data for the reference year 2004. A database for emission factors was compiled, and their geometric means and frequency distributions applied for emission calculation and uncertainty analysis, respectively. The results for 37 Countries were compared with other PAH emission inventories. It was estimated that the total global atmospheric emission of these 16 PAHs in 2004 was 520 giga grams per year (Gg y (1)) with biofuel (56.7%), wildfire (17.0%) and consumer product usage (6.9%) as the Major Sources, and China (114 Gg y(-1)), India (90 Gg y (1)) and United States (32 Gg y (1)) were the top three Countries with the highest PAH emissions. The PAH sources in the individual countries varied remarkably. For example, biofuel burning was the dominant PAH source in India, wildfire emissions were the dominant PAH source in Brazil, while consumer products were the major PAH emission Source in the United States. In China, in addition to biomass combusion, coke ovens were a significant Source of PAHs. Globally, benzo(a)pyrene accounted for 0.05% to 2.08% of the total PAH emission, with developing Countries accounting for the higher percentages. The PAH emission density varied dramatically from 0.0013 kg km(-2) y in the Falkland Islands to 360 kg km(-2) y in Singapore with a global mean Value of 3.98 kg km(-2) y. The atmospheric emission of PAHs was positively cot-related to the country's gross domestic product and negatively correlated with average income. Finally, a linear bivariate regression model was developed to explain the global PAH emission data. (C) 2008 Elsevier Ltd. All rights reserved.

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