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Pyrolysis of Mango Residues: A Statistic Analysis on Nonlinear Models Used to Describe the Drying Stage

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Abstract

Mango seeds are a lignocellulosic waste produced in the agroindustry, and they are available in large quantities in tropical countries. A better alternative to employ mango residues is through pyrolysis. Most equations used in the representation of the drying stage of biomass pyrolysis are nonlinear; therefore, estimating parameters based on experimental data requires attention. In some situations, estimators (especially confidence intervals) may not be appropriate. This work presents a drying kinetics study on mango seed shells using thermogravimetric data. Some non-isothermal models were analyzed to predict the drying kinetic behavior, and some nonlinearity measures were used as a tool to correctly estimate the drying kinetic parameters. The drying behavior of this biomass was best described using the Henderson equation, which showed non-significance for bias and nonlinearity measures. Kinetic analysis of pyrolysis was performed using the Ozawa method in a wide range of conversions (0.13–0.75) in the devolatilization stage. The activation energy values found for mango seeds were within the range reported in the literature for lignocellulosic biomass.

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References

  1. Geerkens, C.H., Nagel, A., Meike, K.J., Petra, M.R., Dietmar, R.K., Ralf, M.S., Reinhold, C.: Mango pectin quality as influenced by cultivar, ripeness, peel particle size, blanching, drying, and irradiation. Food Hydro. 51, 241–251 (2015). https://doi.org/10.1016/j.foodhyd.2015.05.022

    Article  Google Scholar 

  2. Henrique, M.A., Silvério, H.A., Flauzino, W.P., Pasquini, D.J.: Valorization of an agro-industrial waste, mango seed, by the extraction and characterization of its cellulose nanocrystals. Environ. Manag. 121, 202–209 (2013). https://doi.org/10.1016/j.jenvman.2013.02.054

    Google Scholar 

  3. Orfão, J.J.M., Antunes, F.J.A., Figueiredo, J.L.: Pyrolysis kinetics of lignocellulosic materials—three independent reactions model. Fuel. 78, 349–358 (1999). https://doi.org/10.1016/S0016-2361(98)00156-2

    Article  Google Scholar 

  4. Santos, K.G., Lobato, F.S., Lira, T.S., Murata, V.V., Barrozo, A.S.M.: Sensitivity analysis applied to independent parallel reaction model for pyrolysis of bagasse. Chem. Eng. Res. Des. 90, 1989–1996 (2012). https://doi.org/10.1016/j.cherd.2012.04.007

    Article  Google Scholar 

  5. Demirbas, A.: Effect of initial moisture content on the yields of oily products from pyrolysis of biomass. J. Anal. Appl. Pyrolysis. 71, 803–815 (2004). https://doi.org/10.1016/j.jaap.2003.10.008

    Article  Google Scholar 

  6. Chen, D., Zheng, Y., Zhu, X.: Determination of effective moisture diffusivity and drying kinetics for poplar sawdust by thermogravimetric analysis under isothermal condition. Bioresour. Technol. 107, 451–455 (2012). https://doi.org/10.1016/j.biortech.2011.12.032

    Article  Google Scholar 

  7. Cai, J.M., Chen, S.Y.: Determination of drying kinetics for biomass by thermogravimetric analysis under nonisothermal condition. Dry. Technol. 26, 1464–1468 (2008). https://doi.org/10.1080/07373930802412116

    Article  Google Scholar 

  8. Chen, D.Y., Zhang, Y., Zhu, X.F.: Drying kinetics of rice straw under isothermal and nonisothermal conditions: a comparative study by thermogravimetric analysis. Energy Fuels. 26, 4189–4194 (2012). https://doi.org/10.1021/ef300424n

    Article  Google Scholar 

  9. Lira, T.S., Santos, K.G., Murata, V.V., Gianesella, M., Barrozo, M.A.S.: The use of nonlinearity measures in the estimation of kinetic parameters of sugarcane bagasse pyrolysis. Chem. Eng. Technol. 33, 1699–1705 (2010). https://doi.org/10.1002/ceat.201000137

    Article  Google Scholar 

  10. Arnosti, Jr.S., Freire, J.T., Sartori, D.J.M., Barrozo, M.A.S.: Equilibrium moisture content of Brachiaria brizantha. Seed Sci.Technol. 27, 273–282 (1999). https://doi.org/10.1002/fsn3.67

    Google Scholar 

  11. Box, M.J.: Bias in nonlinear estimation. J. R. Statist. Soc. 33(B), 171–201 (1971). http://www.jstor.org/stable/2985002

  12. Bates, D.M., Watts, D.G.: Relative curvature measures of nonlinearity. J. R. Statist. Soc. 42, 1–25 (1980). http://www.jstor.org/stable/2984733

  13. Barrozo, M.A.S., Freire, F.B., Sartori, D.J.M., Freire, J.T.: Study of the drying kinetics in thin layer: fixed and moving bed. Dry. Technol. 23(7), 1451–1464 (2005). https://doi.org/10.1081/DRT-200063508

    Article  Google Scholar 

  14. Barrozo, M.A.S., Sartori, D.J.M., Freire, J.T., Achcar, J.A.: Discrimination of equilibrium moisture equations for soybean using nonlinearity measures. Dry. Technol. 14(7), 1779–1794 (1996). https://doi.org/10.1080/07373939608917173

    Article  Google Scholar 

  15. Ribeiro, J.A., Oliveira, D.T., Passos, M.L., Barrozo, M.A.S.J.: The use of nonlinearity measures to discriminate the equilibrium moisture equations for Bixa orellana seeds. Food Eng. 66(1), 63–68 (2005). https://doi.org/10.1016/j.jfoodeng.2004.02.040

    Article  Google Scholar 

  16. Bortoli, C.T., Barrozo, M.A.S.: Searching the best equilibrium moisture equation for lettuce seeds using measures of curvature and bias. Food Sci. Nutr. 1(6), 422–427 (2013). https://doi.org/10.1002/fsn3.67

    Article  Google Scholar 

  17. Vekemans, O., Laviolette, J.P., Chaouki, J.: Thermal behavior of an engineered fuel and its constituents for a large range of heating rates with emphasis on heat transfer limitations. Thermochim. Acta. 601, 54–62 (2015). https://doi.org/10.1016/j.tca.2014.12.007

    Article  Google Scholar 

  18. Vega-Gálvez, A., Miranda, M., Díaz, L.P., Lopez, L., Rodriguez, K., Di Scala, K.: Effective moisture diffusivity determination and mathematical modelling of the drying curves of the olive-waste cake. Bioresour. Technol. 101, 7265–7270 (2010). https://doi.org/10.1016/j.biortech.2010.04.040

    Article  Google Scholar 

  19. Riegel, I., Moura, A.B.D., Morisso, F.D.P., Mello, F.S.J.: Thermogravimetric analysis of black acacia pyrolysis (Acacia mearnsii de Wild.) cultivated in Rio Grande do Sul, Brazil. Rev. Árvore. 32, 533–543 (2008). https://doi.org/10.1590/S0100-67622008000300014

    Article  Google Scholar 

  20. Sanchez, M.E., Otero, M., Gómez, X., Morán, A.: Thermogravimetric kinetic analysis of the combustion of biowastes. Renew. Energy. 34, 1622–1627 (2009). https://doi.org/10.1016/j.renene.2008.11.01

    Article  Google Scholar 

  21. Yao, F., Wu, Q., Lei, Y., Guo, W., Xu, Y.: Thermal decomposition kinetics of natural fibers: activation energy with dynamic thermogravimetric analysis. Polym. Degrad. Stab. 93, 90–98 (2008). https://doi.org/10.1016/j.polymdegradstab.2007.10.012

    Article  Google Scholar 

  22. Moreno, R.M.B., Medeiros, E.S., Ferreira, F.C., Alves, N., Gonçalves, P., Mattoso, L.H.C.: Thermogravimetric studies of decomposition kinetics of six different IAC Hevea rubber clones using Flynn–Wall–Ozawa approach. Plast. Rubber Compos. 35, 15–21 (2006). https://doi.org/10.1179/174328906X79932

    Article  Google Scholar 

  23. Seber, G.A.F., Wild, J.: Nonlinear Regression. Wiley, New York (1998)

    MATH  Google Scholar 

  24. Ratkowsky, D.A.: Nonlinear Regression Modeling. Marcel Dekker Inc., New York (1993)

    MATH  Google Scholar 

  25. Fernandes, N.J., Ataíde, C.H., Barrozo, M.A.S.: Modeling and experimental study of hydrodynamic and drying characteristics of an industrial rotary dryer. Braz. J. Chem. Eng. 26, 331 (2009)

    Article  Google Scholar 

  26. Erbay, Z., Icier, F.: A review of thin layer drying of foods: theory modeling, and experimental results. Crit. Rev. Food Sci. Nutr. 50, 441–464 (2010). https://doi.org/10.1080/10408390802437063

    Article  Google Scholar 

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Acknowledgements

The authors thank to the Brazilian research funding agencies CNPq, FAPEMIG and CAPES for their financial support to this research.

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Correspondence to L. G. M. Vieira.

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Andrade, L.A., Barrozo, M.A.S. & Vieira, L.G.M. Pyrolysis of Mango Residues: A Statistic Analysis on Nonlinear Models Used to Describe the Drying Stage. Waste Biomass Valor 10, 2335–2342 (2019). https://doi.org/10.1007/s12649-018-0243-8

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  • DOI: https://doi.org/10.1007/s12649-018-0243-8

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