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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 6
Atmos. Chem. Phys., 10, 2937–2946, 2010
https://doi.org/10.5194/acp-10-2937-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Chemistry, Emission, and Transport of Atmospheric Mercury...

Atmos. Chem. Phys., 10, 2937–2946, 2010
https://doi.org/10.5194/acp-10-2937-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

  29 Mar 2010

29 Mar 2010

Uncertainties in estimating mercury emissions from coal-fired power plants in China

Y. Wu1, D. G. Streets2, S. X. Wang1, and J. M. Hao1 Y. Wu et al.
  • 1Department of Environmental Science and Engineering, and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
  • 2Decision and Information Sciences Division, Argonne National Laboratory, Argonne, Illinois 60439, USA

Abstract. A detailed multiple-year inventory of mercury emissions from anthropogenic activities in China has been developed. Coal combustion and nonferrous metals production continue to be the two leading mercury sources in China, together contributing ~80% of total mercury emissions. However, many uncertainties still remain in our knowledge of primary anthropogenic releases of mercury to the atmosphere in China. In situations involving large uncertainties, our previous mercury emission inventory that used a deterministic approach could produce results that might not be a true reflection of reality; and in such cases stochastic simulations incorporating uncertainties need to be performed. Within our inventory, a new comprehensive sub-module for estimation of mercury emissions from coal-fired power plants in China is constructed as an uncertainty case study. The new sub-module integrates up-to-date information regarding mercury content in coal by province, coal washing and cleaning, coal consumption by province, mercury removal efficiencies by control technology or technology combinations, etc. Based on these detailed data, probability-based distribution functions are built into the sub-module to address the uncertainties of these key parameters. The sub-module incorporates Monte Carlo simulations to take into account the probability distributions of key input parameters and produce the mercury emission results in the form of a statistical distribution. For example, the best estimate for total mercury emissions from coal-fired power plants in China in 2003 is 90.5 Mg, with the uncertainty range from 57.1 Mg (P10) to 154.6 Mg (P90); and the best estimate for elemental mercury emissions is 43.0 Mg, with the uncertainty range from 25.6 Mg (P10) to 75.7 Mg (P90). The results further indicate that the majority of the uncertainty in mercury emission estimation comes from two factors: mercury content of coal and mercury removal efficiency.

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