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Utilisation of a waste biomass, walnut shells, to produce bio-products via pyrolysis: investigation using ISO-conversional and neural network methods

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Abstract

This study was conducted to investigate the kinetic, thermodynamics and the reaction mechanism of pyrolysis of native walnut shells of Kashmir, India. Thermal degradation experiments were performed at three heating rates of 10, 25, and 50 K min−1 to calculate the kinetic and thermodynamic parameters, using iso-conversional Kissinger-Akahira-Sunrose (KAS) and Ozawa-Flynn-Wall (OFW) models. The reaction mechanism was predicted by applying Coats-Redfern (CR) method. Moreover, an artificial neural network (ANN) simulation was used to obtain best fit points after comparing the experimental data with the predicted data points. Average activation energy was calculated from the thermogravimetric study was found to be in the range of 146.03–148.89 kJ mol−1, while the Gibbs free energy (ΔG) value for walnut shells was found to be ~180 kJ mol−1. The most appropriate degradation mechanism was found to be based on diffusion and chemical reaction for the temperature range under study. The broad characterisation along with the values of thermodynamic parameters show that the walnut shells can be used as an economical as well as eco-friendly bio-energy feed-stock for pyrolysis. The reaction mechanism of thermal degradation of walnut shells was found to be consisting of two broader zones based on conversion achieved, zone I (0.2 ≤ α ≤ 0.4) and zone II (0.4 ≤ α ≤ 0.8).

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Abbreviations

A o :

Pre-exponential factor, s−1

ANN:

Artificial neural network

CR:

Coats-Redfern method

D1–5:

Diffusion-based mechanisms

DTA:

Differential thermal analysis

DTG:

Differential thermogravimetry

E t :

Activation energy, kJ mol−1

F1–5:

Chemical reaction-based mechanism

HHV:

High heating value, MJ g−1

k (T):

Reaction rate constant

K b :

Boltzman constant, 1.381 × 10−23 J K−1

KAS:

Kissinger-Akahira-Sunrose

MSE:

Mean square error

OFW:

Ozawa-Flynn-Wall method

o :

Output values

R1–5:

Contacting geometry-based mechanism

t :

Target values

α :

Conversion

∆G :

Gibbs free energy, kJ mol−1

∆H :

Change in enthalpy, kJ mol−1

References

  1. Abnisa F, Arami-Niya A, Daud WMAW, Sahu JN, Noor IM (2013) Utilization of oil palm tree residues to produce bio-oil and bio-char via pyrolysis. Energy Convers Manag 76:1073–1082

    Article  Google Scholar 

  2. Ningbo G, Baoling L, Aimin L, Juanjuan L (2015) Continuous pyrolysis of pine sawdust at different pyrolysis temperatures and solid residence times. J Anal App Pyrol 114:155–162

    Article  Google Scholar 

  3. Mukherjee A, Das P, Minu K (2014) Thermogravimetric analysis and kinetic modelling studies of selected agro-residues and biodiesel industry wastes for pyrolytic conversion to bio-oil. Biomass Conv Bioref 4:259–258

    Article  Google Scholar 

  4. Pradhan RR, Garnaik PP, Regmi B, Dash B, Dutta A (2017) Pyrolysis kinetics of sal (Shorea robusta) seeds. Biomass Conv Bioref 7:237–247

    Article  Google Scholar 

  5. Acikalm K (2011) Thermogravimetric analysis of walnut shell as pyrolysis feedstock. J Therm Anal Calorim 105:145–150

    Article  Google Scholar 

  6. Demirbas A (2006) Effect of temperature on pyrolysis products from four nut shells. J Anal Appl Pyrol 76:285–289

    Article  Google Scholar 

  7. Yuan HR, Liu RH (2007) Study on pyrolysis kinetics of walnut shell. J Therm Anal Calorim 89-3:983–986

    Article  Google Scholar 

  8. Cai JM, Wu WX, Liu RH, Huber GW (2013) A distributed activation energy model for the pyrolysis of lignocellulosic biomass. Green Chem 15:1331–1340

    Article  Google Scholar 

  9. Wu W, Mei Y, Zhang L, Liu R, Cai J (2014) Effective activation energies of lignocellulosic biomass pyrolysis. Energ Fuel 28:3916–3923

    Article  Google Scholar 

  10. Irdem SD, Parparita E, Vasile C, Uddin MA, Yanik J (2014) Steam reforming of tar derived from walnut shell and almond shell gasification on red mud and iron-ceria catalysts. Energ Fuel 28:3808–3813

    Article  Google Scholar 

  11. Kalogirou SA (2003) Artificial intelligence for the modeling and control of combustion processes: a review. Prog Energy Combust Sci 29:515–566

    Article  Google Scholar 

  12. Ahmad MS, Mehmood MA, Taqvi STH, Elkamel A, Liu C, Xu J, Rahimuddin SA, Gull M (2017) Pyrolysis, kinetics analysis, thermodynamics parameters and reaction mechanism of Typha latifolia to evaluate its bioenergy potential. Bioresour Technol 245:491–501

    Article  Google Scholar 

  13. Yıldız Z, Uzun H, Ceylan S, Topcu Y (2016) Application of artificial neural networks to co-combustion of hazelnut husk–lignite coal blends. Bioresour Technol 200:42–47

    Article  Google Scholar 

  14. Sharma RM, Kour K, Singh B, Yadav S, Kotwal N, Rana JC, Anand R (2014) Selection and characterization of elite walnut (Juglans regia L.) clone from seedling origin trees in North Western Himalayan region of India. Aust J Crop Sci 8(2):257–262

    Google Scholar 

  15. Sharma R (2012) Area and production database of fruit crops. Directorate of hortic state department of horticulture. Jammu and Kashmir government, Srinagar, India

    Google Scholar 

  16. Uzun BB, Yaman E (2014) Thermogravemetric characteristics and kinetics of scrap tyre and juglans regia shell co-pyrolysis. Waste Manage Res 32(10):961–970

    Article  Google Scholar 

  17. Akahira T, Sunrose T (1969) Transactions of Joint Convention of Four Electrical Institutes. 246

  18. Flynn JH, Wall LA (1966) A quick, direct method for the determination of activation energy from thermogravimetric Data. J Polym Sci Pol Lett 5:323–328

    Article  Google Scholar 

  19. Ozawa T (1965) A new method of analyzing thermogravimetric data. Bull Chem Soc Japan 38:1881–1886

    Article  Google Scholar 

  20. Chen D, Zhou J, Zhang Q (2014) Effects of torrefaction on the pyrolysis behaviour and bio-oil properties of rice husk by using TG-FTIR and Py-GC/MS. Energ Fuel 28:5857–5863

    Article  Google Scholar 

  21. Doyle CD (1965) Series approximations to the equations of thermo-gravimetric data. Nature 207:290–291

    Article  Google Scholar 

  22. Damartzis T, Vamvuka D, Sfakiotakis S, Zabaniotou A (2011) Thermal degradation studies and kinetic modelling of cardoon (Cynaracardunculus) pyrolysis using thermogravimetric analysis (TGA). Bioresour Technol 102(10):6230–6238

    Article  Google Scholar 

  23. Ceylan S, Topcu Y (2014) Pyrolysis kinetics of hazelnut husk using thermo-gravimetric analysis. Bioresour Technol 156:182–188

    Article  Google Scholar 

  24. Mythili R, Venkatachalam P, Subramanian P, Uma D (2013) Characterization of bio residues for bio oil production through pyrolysis. Biresourc Technol 138:71–78

    Article  Google Scholar 

  25. Toshniwal P, Srivastava VC (2017) Existence of synergistic effects during co-pyrolysis of petroleum coke and wood pellet. Intl J Chem React Eng 20160046:1–12

    Google Scholar 

  26. El-Sayed SA, Mostafa ME (2015) Kinetic parameters determination of biomass pyrolysis fuels using TGA and DTA Techniques. Waste Biomass Valori 6:401–415

    Article  Google Scholar 

  27. Ferreira CIA, Calisto V, Cuerda-Correa EM, Otero M, Nadais H, Esteves VI (2016) Comparative valorisation of agricultural and industrial bio wastes by combustion and pyrolysis. Bioresour Technol 218:918–925

    Article  Google Scholar 

  28. Kilic M, Kirbiyik C, Cepeliogullar O, Putun AE (2013) Adsorption of heavy metal ions from aqueous solutions by bio-char, a by-product of pyrolysis. Appl Surf Sci 283:856–862

    Article  Google Scholar 

  29. Dandekar A, Baker RTK, Vannice MA (1998) Characterization of activated carbon, graphitized carbon fibres and synthetic diamond power using TPD and DRIFTS. Carbon 36:1821–1831

    Article  Google Scholar 

  30. Hanafiah MAKM, Ngah WSW, Zolkafly SH, Teong LC, Majid ZA (2012) Acid Blue 25 adsorption on base treated Shorea dasyphylla sawdust: Kinetic, isotherm, thermodynamic and spectroscopic analysis. J Environ Sci 24:261–268

    Article  Google Scholar 

  31. Yang J, Fang F, Zhou J (2013) Effect of microstructure and surface chemistry in liquid-phase adsorptive nicotine by almond-shell-based activated carbon. Chinese Sci Bull 58(30):3715–3720

    Article  Google Scholar 

  32. Grube M, Lin J, Lee P, Kokorevicha S (2006) Evaluation of sewage sludge-based compost by FT-IR spectroscopy. Geoderma 130:324–333

    Article  Google Scholar 

  33. Mehmood MA, Ye G, Luo H, Liu C, Malik S, Afzal I, Xu J, Ahmad MS (2017) Pyrolysis and kinetic analyses of camel grass (Cymbopogon schoenanthus) for bioenergy. Bioresour Technol 228:18–24

    Article  Google Scholar 

  34. Braga RM, Melo DM, Aquino FM, Freitas JC, Melo MA, Barros JM, Fontes MS (2014) Characterization and comparative study of pyrolysis kinetics of the rice husk and the elephant grass. J Therm Anal Calorim 115(2):1915–1920

    Article  Google Scholar 

  35. Kim YS, Kim YS, Kim SH (2010) Investigation of thermodynamic parameters in the thermal decomposition of plastic waste–waste lube oil compounds. Environ Sci Technol 44:5313–5317

    Article  Google Scholar 

  36. Xu Y, Chen B (2013) Investigation of thermodynamic parameters in the pyrolysis conversion of biomass and manure to biochars using thermogravimetric analysis. Bioresource Technol 146:485–493

    Article  Google Scholar 

  37. Vlaev L, Georgieva V, Genieva S (2007) Products and kinetics of non-isothermal decomposition of vanadium (IV) oxide compounds. J Therm Anal Calorim 88:805–812

    Article  Google Scholar 

  38. Turmanova SC, Genieva S, Dimitrova A, Vlaev L (2008) Non-isothermal degradationkinetics of filled with rise husk ash polypropene composites. Express Polym Lett 2:133–146

    Article  Google Scholar 

  39. Maia AAD, de Morais LC (2016) Kinetic parameters of red pepper waste as biomass to solid biofuel. Bioresour Technol 204:157–163

    Article  Google Scholar 

  40. Khawam A, Flanagan DR (2006) Solid-state kinetic models: basics and mathematical fundamentals. J Phys Chem B 110:17315–17328

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Chemical Engineering, National Institute of Technology Srinagar, Srinagar, 190006, India

    Tanveer Rasool & M. N. S. Khan

  2. Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, India

    Vimal Chandra Srivastava

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  1. Tanveer Rasool
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Correspondence to Vimal Chandra Srivastava.

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Rasool, T., Srivastava, V.C. & Khan, M.N.S. Utilisation of a waste biomass, walnut shells, to produce bio-products via pyrolysis: investigation using ISO-conversional and neural network methods. Biomass Conv. Bioref. 8, 647–657 (2018). https://doi.org/10.1007/s13399-018-0311-0

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