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Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes

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  • Huang, Youwang
  • Wang, Haiyong
  • Zhang, Xinghua
  • Zhang, Qi
  • Wang, Chenguang
  • Ma, Longlong

Abstract

The exergy-based assessment on the sustainable utilization processes of technical lignin is important for potential identify and process optimization. In this study, chemical exergy of technical lignin was evaluated for the first time based on the Gibbs free energy relation. The chemical exergy of technical lignin was from 17653.89 to 33337.92 kJ kg−1.The effects of O/C and H/C ratios on the chemical exergy and standard entropy were investigated by using contour plot analysis. The chemical exergy of technical lignin is more significantly influenced by the O/C ratio, compared with the H/C ratio. Three types of prediction models including artificial neural network model with the input of elemental composition, HHV-based correlation, and element-based correlation were developed. The artificial neural network model has an excellent performance of predicting the chemical exergy of technical lignin, with the prediction relative error of less than ±0.15% under the confidential level of 97%. The prediction relative errors of the HHV-based correlation and the element-based correlation are within ±1.0% and ±2.5%, respectively. This work will provide the basic data for exergy-based assessment on the valorization processes of technical lignin, which is an important aspect of improving the economic level of biorefinery industry.

Suggested Citation

  • Huang, Youwang & Wang, Haiyong & Zhang, Xinghua & Zhang, Qi & Wang, Chenguang & Ma, Longlong, 2022. "Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes," Energy, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:energy:v:243:y:2022:i:c:s0360544221032904
    DOI: 10.1016/j.energy.2021.123041
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    References listed on IDEAS

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    1. Huang, Y.W. & Chen, M.Q. & Li, Y. & Guo, J., 2016. "Modeling of chemical exergy of agricultural biomass using improved general regression neural network," Energy, Elsevier, vol. 114(C), pages 1164-1175.
    2. Bilgen, Selçuk & Keleş, Sedat & Kaygusuz, Kamil, 2012. "Calculation of higher and lower heating values and chemical exergy values of liquid products obtained from pyrolysis of hazelnut cupulae," Energy, Elsevier, vol. 41(1), pages 380-385.
    3. Charalampos Michalakakis & Jeremy Fouillou & Richard C. Lupton & Ana Gonzalez Hernandez & Jonathan M. Cullen, 2021. "Calculating the chemical exergy of materials," Journal of Industrial Ecology, Yale University, vol. 25(2), pages 274-287, April.
    4. Gharagheizi, Farhad & Ilani-Kashkouli, Poorandokht & Mohammadi, Amir H. & Ramjugernath, Deresh, 2014. "A group contribution method for determination of the standard molar chemical exergy of organic compounds," Energy, Elsevier, vol. 70(C), pages 288-297.
    5. Lee, Cornelius Basil Tien Loong & Wu, Ta Yeong, 2021. "A review on solvent systems for furfural production from lignocellulosic biomass," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    6. Ha, Jeong-Myeong & Hwang, Kyung-Ran & Kim, Young-Min & Jae, Jungho & Kim, Kwang Ho & Lee, Hyung Won & Kim, Jae-Young & Park, Young-Kwon, 2019. "Recent progress in the thermal and catalytic conversion of lignin," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 422-441.
    7. Marathe, P.S. & Westerhof, R.J.M. & Kersten, S.R.A., 2019. "Fast pyrolysis of lignins with different molecular weight: Experiments and modelling," Applied Energy, Elsevier, vol. 236(C), pages 1125-1137.
    8. Martínez, Amaya & Uche, Javier, 2010. "Chemical exergy assessment of organic matter in a water flow," Energy, Elsevier, vol. 35(1), pages 77-84.
    9. Song, Guohui & Xiao, Jun & Zhao, Hao & Shen, Laihong, 2012. "A unified correlation for estimating specific chemical exergy of solid and liquid fuels," Energy, Elsevier, vol. 40(1), pages 164-173.
    10. Xiaona Lin & Shujuan Sui & Shun Tan & Charles U. Pittman & Jianping Sun & Zhijun Zhang, 2015. "Fast Pyrolysis of Four Lignins from Different Isolation Processes Using Py-GC/MS," Energies, MDPI, vol. 8(6), pages 1-15, June.
    11. Bilgen, Selçuk & Kaygusuz, Kamil, 2008. "The calculation of the chemical exergies of coal-based fuels by using the higher heating values," Applied Energy, Elsevier, vol. 85(8), pages 776-785, August.
    12. Huang, Y.W. & Chen, M.Q. & Li, Q.H. & Xing, W., 2018. "A critical evaluation on chemical exergy and its correlation with high heating value for single and multi-component typical plastic wastes," Energy, Elsevier, vol. 156(C), pages 548-554.
    13. Gharagheizi, Farhad & Ilani-Kashkouli, Poorandokht & Hedden, Ronald C., 2018. "Standard molar chemical exergy: A new accurate model," Energy, Elsevier, vol. 158(C), pages 924-935.
    14. Qian, Hongliang & Zhu, Weiwei & Fan, Sudong & Liu, Chang & Lu, Xiaohua & Wang, Zhixiang & Huang, Dechun & Chen, Wei, 2017. "Prediction models for chemical exergy of biomass on dry basis from ultimate analysis using available electron concepts," Energy, Elsevier, vol. 131(C), pages 251-258.
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