Skip to main content

Syngas Assessment from Plastic Waste Using Artificial Neural Network—A Review

  • Conference paper
  • First Online:
Machine Learning for Predictive Analysis

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 141))

Abstract

On our planet, pollution is one of the major issues for humankind. Pollutions like, pollution of land, pollution of water, pollution of air, pollution of noise, and many other types of pollution are directly or indirectly affect on humankind. Due to this pollution, our planet got global warming effect, climate change, and also very hazardous effect on human body due to air pollution, and also the issue of waste product dumping that creates the land pollution. Plastic plays one of the most important roles for land pollution. Plastic waste which does not decompose naturally in the environment causes pollution. Plastic also affects on wild life, in land due to plastic pollution, rainwater not able to go at the desired level, and plastic also affects the farming, due to plastic pollution in land. Crops are not able to get the desired nutrition from land. The survey from the literature available found that with the help of gasification and pyrolysis process can change waste plastic as a transportation fuel and also solve the problem of dumping of plastic waste. The quality of syngas is using the ANN model. The production of syngas, and gasification techniques was widely used, and for the quality of improvement of syngas, various techniques reported in the literature review.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Plastics Europe, Plastics—The Facts 2014/2015: An Analysis of European Plastics Production, Demand and Waste Data (Plastics Europe, 2015), pp. 1–34

    Google Scholar 

  2. V.E. Yarsley, E.G. Couzens, Plastics in the Modern World (Penguin, Baltimore, MD, 1945)

    Google Scholar 

  3. R.C. Thompson, C.J. Moore, F.S. vom Saal, S.H. Swan, Plastics, the environment and human health: current consensus and future trends. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364, 2153–2166 (2009)

    Google Scholar 

  4. A.L. Andrady, M.A. Neal, Applications and societal benefits of plastics. Philos. Trans. R. Soc. B Biol. Sci. 364, 1977–1984 (2009). www.learn.eartheasy.com

  5. I. Kalargaris, G. Tian, S. Gu, Investigation on the long-term effects of plastic pyrolysis oil usage in a diesel engine. Energ. Procedia 142, 49–54 (2017)

    Google Scholar 

  6. J.J. Adibi, F.P. Perera, W. Jedrychowski, D.E. Camann, D. Barr, R. Jacek et al., Prenatal exposures to phthalates among women in New York and Krakow, Poland. Environ. Health Perspect. 111, 1719–1722 (2003)

    Google Scholar 

  7. S.M. Al-Salem, P. Lettieri, J. Baeyens, Recycling and recovery routes of plastic solid waste (PSW): a review. Waste Manag. 29, 2625–2643 (2009)

    Google Scholar 

  8. M. Sadat-Shojai, G.R. Bakhshandeh, Recycling of PVC wastes. Polym. Degrad. Stab. 96, 404–415 (2011)

    Google Scholar 

  9. S.R. Chandrasekaran, B. Kunwar, B.R. Moser, N. Rajagopalan, B.K. Sharma, Catalytic thermal cracking of postconsumer waste plastics to fuels. 1. Kinetics and optimization. Energ. Fuels 29, 6068–6077 (2015)

    Google Scholar 

  10. A. Tavasoli et al., Sugarcane bagasse supercritical water gasification in presence of potassium promoted copper nano-catalysts supported on g-Al2O3. Int. J. Hydrogen Energ. (2015). https://doi.org/10.1016/j.ijhydene.2015.09.026

    Article  Google Scholar 

  11. R.S.S. Prabhahar, P. Nagaraj, K. Jeyasubramanian, Enhanced recovery of H2 gas from rice husk and its char enabled with nano catalytic pyrolysis/gasification. Microchem. J. https://doi.org/10.1016/j.microc.2019.02.024

  12. J. George, P. Arun, C. Muraleedharan, Assessment of producer gas composition in air gasification of biomass using artificial neural network model. Int. J. Hydrogen Energ. 43, 9558–9568 (2018)

    Google Scholar 

  13. A. Karaci, A. Caglar, B. Aydinli, S. Pekol, The pyrolysis process verification of hydrogen rich gas (HerG) production by artificial neural network (ANN). Int. J. Hydrogen Energ. 41, 4570–4578 (2016)

    Google Scholar 

  14. D. Baruah, D.C. Baruah, M.K. Hazarika, Artificial neural network based modeling of biomass gasification in fixed bed downdraft gasifiers. Biomass Bioenerg. 98, 264–271 (2017)

    Google Scholar 

  15. D.S. Pandey, S. Das, I. Pan, J.J. Leahy, W. Kwapinski, Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor. Waste Manag. (2016)

    Google Scholar 

  16. G. Xiao, M. Ni, Y. Chi, B. Jin, R. Xiao, Z. Zhong, Y. Huang, Gasification characteristics of MSW and an ANN prediction model. Waste Manag. (2009)

    Google Scholar 

  17. M. Shahbaz, S.A. Taqvi, A.C.M. Loy, A. Inayat, F. Uddin, A. Bokhari, S.R. Naqvi, Artificial neural network approach for the steam gasification of palm oil waste using bottom ash and CaO. Renew. Energ. (2018)

    Google Scholar 

  18. M. Puig-Arnavat, J. Alfredo Hernández, J.C. Bruno, A. Coronas, Artificial neural network models for biomass gasification in fluidized bed gasifiers. Biomass Bioenerg. 49, 279–289 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Maulik A. Modi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Modi, M.A., Patel, T.M. (2021). Syngas Assessment from Plastic Waste Using Artificial Neural Network—A Review. In: Joshi, A., Khosravy, M., Gupta, N. (eds) Machine Learning for Predictive Analysis. Lecture Notes in Networks and Systems, vol 141. Springer, Singapore. https://doi.org/10.1007/978-981-15-7106-0_20

Download citation

Publish with us

Policies and ethics