Title: Russian anthropogenic black carbon: Emission reconstruction and Arctic black carbon simulation

Abstract

Development of reliable source emission inventories is needed to advance the understanding of the origin of Arctic haze using chemical transport modeling. This paper develops a regional anthropogenic black carbon (BC) emission inventory for the Russian Federation, the largest country by land area in the Arctic Council. Activity data from combination of local Russia information and international resources, emission factors based on either Russian documents or adjusted values for local conditions, and other emission source data are used to approximate the BC emissions. Emissions are gridded at a resolution of 0.1° × 0.1° and developed into a monthly temporal profile. Total anthropogenic BC emission of Russia in 2010 is estimated to be around 224 Gg. Gas flaring, a commonly ignored black carbon source, contributes a significant fraction of 36.2% to Russia's total anthropogenic BC emissions. Other sectors, i.e., residential, transportation, industry, and power plants, contribute 25.0%, 20.3%, 13.1%, and 5.4%, respectively. Three major BC hot spot regions are identified: the European part of Russia, the southern central part of Russia where human population densities are relatively high, and the Urals Federal District where Russia's major oil and gas fields are located but with sparse human population. BC simulations are conductedmore » using the hemispheric version of Community Multi-scale Air Quality Model with emission inputs from a global emission database EDGAR (Emissions Database for Global Atmospheric Research)-HTAPv2 (Hemispheric Transport of Air Pollution) and EDGAR-HTAPv2 with its Russian part replaced by the newly developed Russian BC emissions, respectively. The simulation using the new Russian BC emission inventory could improve 30–65% of absorption aerosol optical depth measured at the AERONET sites in Russia throughout the whole year as compared to that using the default HTAPv2 emissions. At the four ground monitoring sites (Zeppelin, Barrow, Alert, and Tiksi) in the Arctic Circle, surface BC simulations are improved the most during the Arctic haze periods (October–March). The poor performance of Arctic BC simulations in previous studies may be partly ascribed to the Russian BC emissions built on out-of-date and/or missing information, which could result in biases to both emission rates and the spatial distribution of emissions. Finally, this study highlights that the impact of Russian emissions on the Arctic haze has likely been underestimated, and its role in the Arctic climate system needs to be reassessed. The Russian black carbon emission source data generated in this study can be obtained via http://abci.ornl.gov/download.shtml or http://acs.engr.utk.edu/Data.php.« less

Authors:

Huang, Kan ^[1]; Fu, Joshua S. ^[1]; Prikhodko, Vitaly Y. ^[2]; Storey, John M. ^[2]; Romanov, Alexander ^[3]; Hodson, Elke L. ^[4]; Cresko, Joe ^[5]; Morozova, Irina ^[3]; Ignatieva, Yulia ^[3]; Cabaniss, John ^[5]

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+ Show Author Affiliations

1. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Civil and Environmental Engineering
2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Energy and Environmental Sciences Directorate
3. Scientific Research Inst. for Atmospheric Air Protection, Saint-Petersburg (Russia)
4. Dept. of Energy (DOE), Washington DC (United States)
5. Dept. of Energy (DOE), Washington DC (United States

Publication Date:

2015-10-02

Research Org.:

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:

USDOE; Department of State (United States)

OSTI Identifier:

1261271

Grant/Contract Number:  

AC05-00OR22725; S-OES-11_IAA- 0027

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Geophysical Research: Atmospheres

Additional Journal Information:

Journal Volume: 120; Journal Issue: 21; Journal ID: ISSN 2169-897X

Publisher:

American Geophysical Union

Country of Publication:

United States

Language:

English

Subject:

97 MATHEMATICS AND COMPUTING; 54 ENVIRONMENTAL SCIENCES