Compositional Data Analysis of Coal Combustion Products with an Application to a Wyoming Power Plant

  • J. A. Martín-Fernández
  • R. A. Olea
  • L. F. Ruppert
Article
  • 36 Downloads

Abstract

A mathematically sound approach for summarizing chemical analyses of feed coal and all its combustion products (bottom ash, economizer fly ash, and fly ash) is presented. The nature of the data requires the application of compositional techniques when conducting statistical analysis, techniques that have not been applied before to the study of partitioning of elements between the coal that enters the boiler and the associated coal combustion products. A collection of descriptive and inferential compositional techniques was used to analyze the coal combustion products from a Wyoming power plant burning Paleocene Wyodak–Anderson coal. The significance of the fluctuation in ash composition is determined by using a Hotelling’s T-squared test and bootstrapping. Tree displays allow for visualization of the progressive effect of filters in removal of chemical species based on their geochemical composition. Results indicate that, in general, as the suspended combustion products entrained in the flue gases move closer to the stack, chemical species are removed from the combustion gas, starting with minerals associated with elements having the lowest volatility.

Keywords

Ash Balances Isometric log ratio Perturbation Precipitator Simplex 

Notes

Acknowledgments

The authors wish to thank Mark Engle (USGS) and Vera Pawlowsky-Glahn (University of Girona) for their review and suggestions, which helped improve the manuscript. This work has been supported by the project “CODA-RETOS” (Spanish Ministry of Economy and Competitiveness; Ref. MTM2015-65016-C2-1-R) and the project “Compositional Data Analysis Related to Energy Resources Modeling” (“Salvador de Madariaga” program; “Fulbright” distinction; MECD; Ref. PRX16/00258). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

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Copyright information

© International Association for Mathematical Geosciences 2018

Authors and Affiliations

  1. 1.U.S. Geological SurveyRestonUSA
  2. 2.Department Informàtica, Matemàtica Aplicada i EstadísticaUniversitat de GironaGironaSpain

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