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Waste and Biomass Valorization

, Volume 10, Issue 12, pp 3845–3856 | Cite as

A Method to Forecast the Combustion Characteristics of Biomass Waste: Based on a Custom-Designed Macro-TGA

  • Jundian Luo
  • Qinghai LiEmail author
  • Aihong Meng
  • Yanqiu Long
  • Yanguo ZhangEmail author
Original Paper
  • 182 Downloads

Abstract

The combustion characteristics of five model biomass components (cellulose, hemicellulose, lignin, pectin and starch) and four real biomass waste (poplar stem, Chinese cabbage, orange peel and ginkgo leaf) were evaluated in a custom-designed macro-TGA at three different heating rates. With the increase in the heating rates, the peaks of the various samples in DTG curves shifted to the high temperature region. All main peaks temperature of 20 °C/min were 40–55 °C higher than that of 10 °C/min and 30–40 °C lower than that of 30 °C/min in the combustion on macro-TGA, except for lignin. Furthermore, the pseudo-component model based on the macro-TG curves simulation was analyzed and three/five components simulating results were compared. The overlap ratios between actual macro-TG curves and fitting curves by different methods and heating rates were all higher than 0.979 to suggest that biomass waste combustion characteristics could be well simulated by its components, and the three and five components fitting effects differed for the specific material because of its composition. The TG curves of real biomasses at one heating rate were used to gain the fitting TG curves of other heating rates and forecast their combustion characteristics. The forecast method showed good results but they varied among the biomasses. It might be due to their composition and the interactions among the biomass model components. The pseudo-component model provides a potential method to forecast the combustion characteristics of biomass waste in the MSW incineration.

Keywords

Biomass combustion Pseudo-component model Simulation Overlap ratio Forecast 

Notes

Acknowledgements

This work was supported by the National Key R&D Program of China (Grant No. 2017YFB0603601), and the Tsinghua Student-Counselor Research Fund is also gratefully acknowledged.

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Tsinghua University-University of Waterloo Joint Research Center for Micro/Nano Energy & Environment Technology, Department of Energy and Power EngineeringTsinghua UniversityBeijingPeople’s Republic of China

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