Detail publikace

Modelling the higher heating value of municipal solid waste for assessment of waste-to-energy potential: A sustainable case study

Amen, R., Hameed, J., Albashar, G., Kamran, H.W., Hassan Shah, M.U., Zaman, M.K.U., Mukhtar, A., Saqib, S., Ch, S.I., Ibrahim, M., Ullah, S., Al-Sehemi, A.G., Ahmad, S.R., Klemeš, J.J., Bokhari, A., Asif, S.

Originální název

Modelling the higher heating value of municipal solid waste for assessment of waste-to-energy potential: A sustainable case study

Anglický název

Modelling the higher heating value of municipal solid waste for assessment of waste-to-energy potential: A sustainable case study

Jazyk

en

Originální abstrakt

The municipal solid waste (MSW) is widely considered as a heterogeneous source of energy, with numerous characteristics varying depending on its geographical region or origin from where it is collected. The development of correlations for the prediction of the higher heating value (HHV) of MSW is a sustainable and cleaner way based on data of specific region from where MSW is obtained. In this research, a new approach reported for the development of correlations to predict the energy content of MSW accurately. The developed correlations lie within the all parameter affecting the HHV of MSW. The models presented can predict the HHV of MSW accurately (R2 > 0.8) compared to other models reported in the literature. However, model 13 developed on the basis of ultimate analysis demonstrated maximum accuracy (R2 = 0.919) among all 7 developed models. The aim of developing the prediction model for the HHV of different MSW samples was to reliably predict using proximate or ultimate analytical data to save experimentation costs and provide theoretical foundations for modelling MSW combustion, pyrolysis processes and thermal conversion for the energy security. © 2020 Elsevier Ltd

Anglický abstrakt

The municipal solid waste (MSW) is widely considered as a heterogeneous source of energy, with numerous characteristics varying depending on its geographical region or origin from where it is collected. The development of correlations for the prediction of the higher heating value (HHV) of MSW is a sustainable and cleaner way based on data of specific region from where MSW is obtained. In this research, a new approach reported for the development of correlations to predict the energy content of MSW accurately. The developed correlations lie within the all parameter affecting the HHV of MSW. The models presented can predict the HHV of MSW accurately (R2 > 0.8) compared to other models reported in the literature. However, model 13 developed on the basis of ultimate analysis demonstrated maximum accuracy (R2 = 0.919) among all 7 developed models. The aim of developing the prediction model for the HHV of different MSW samples was to reliably predict using proximate or ultimate analytical data to save experimentation costs and provide theoretical foundations for modelling MSW combustion, pyrolysis processes and thermal conversion for the energy security. © 2020 Elsevier Ltd

Dokumenty

BibTex


@article{BUT168258,
  author="Jiří {Klemeš}",
  title="Modelling the higher heating value of municipal solid waste for assessment of waste-to-energy potential: A sustainable case study",
  annote="The municipal solid waste (MSW) is widely considered as a heterogeneous source of energy, with numerous characteristics varying depending on its geographical region or origin from where it is collected. The development of correlations for the prediction of the higher heating value (HHV) of MSW is a sustainable and cleaner way based on data of specific region from where MSW is obtained. In this research, a new approach reported for the development of correlations to predict the energy content of MSW accurately. The developed correlations lie within the all parameter affecting the HHV of MSW. The models presented can predict the HHV of MSW accurately (R2 > 0.8) compared to other models reported in the literature. However, model 13 developed on the basis of ultimate analysis demonstrated maximum accuracy (R2 = 0.919) among all 7 developed models. The aim of developing the prediction model for the HHV of different MSW samples was to reliably predict using proximate or ultimate analytical data to save experimentation costs and provide theoretical foundations for modelling MSW combustion, pyrolysis processes and thermal conversion for the energy security. © 2020 Elsevier Ltd",
  address="Elsevier Ltd",
  chapter="168258",
  doi="10.1016/j.jclepro.2020.125575",
  howpublished="online",
  institution="Elsevier Ltd",
  number="287",
  year="2021",
  month="march",
  pages="125575--125575",
  publisher="Elsevier Ltd",
  type="journal article in Scopus"
}