Elsevier

Bioresource Technology

Volume 199, January 2016, Pages 362-366
Bioresource Technology

Pyrolysis of microalgae residues – A kinetic study

https://doi.org/10.1016/j.biortech.2015.08.069Get rights and content

Highlights

  • Non-isothermal pyrolysis of microalgae residues.

  • First parallel-model employed for kinetic modelling of microalgae pyrolysis.

  • Five pseudo-components model was applied for kinetic modelling.

  • Protein and lipid were included in the model.

  • The simulation was successful to reflect the kinetic of pyrolysis process.

Abstract

Pyrolysis of residues from the oil extraction process of two types of microalgae, Chlamydomonas (C. sp. JSC4) and Chlorella sorokiniana (C. Sorokiniana CY1) was studied by means of a thermogravimetric analyzer. Five pseudo-components (hemicellulose, cellulose, lignin, lipid and protein) model with n = 1 or n # 1 was assumed for a kinetic analysis of the collected pyrolysis data. The model with n # 1 resulted in a slightly better fit quality and reasonable kinetic parameters. The calculated activation energy of hemicellulose, cellulose, lignin, lipid, protein was 115.12–117.12 kJ/mol, 181.67–198.30 kJ/mol, 61.74–62.75 kJ/mol, 104.93–114.14 kJ/mol and 90.75–99.31 kJ/mol, respectively, for C. sp. JSC4; and 113.12–117.12 kJ/mol, 218.73–28.79 kJ/mol, 64.77–66.39 kJ/mol, 131.97–143.63 kJ/mol and 108.03–118.13 kJ/mol, respectively, for C. Sorokiniana CY1.

Introduction

Microalgae-derived biofuels have been gaining more and more attention because of the capacity (Chen et al., 2015, Patil et al., 2008) to overcome the limitation of the first generation biofuels including the land use conflict and consequently increasing food prices (Patil et al., 2008). Microalgae is an aquatic biomass, therefore the production of microalgae does not compete with food crops. It can be cultivated in marine seawater, freshwater, or even wastewater (Bahadar and Bilal Khan, 2013). Microalgae is also considered as CO2 fixer due to its ability to consume CO2 during the growing process; thus it reduces significant emission of the greenhouse gas (Brown and Zeiler, 1993, Chen et al., 2014b, Gong et al., 2014, Zhu et al., 2014).

After extracting the lipid and other extractives from microalgae biomass, for pharmaceutical chemicals such as Omega 3 and/or for biodiesel production, the residue is normally considered as waste. The residue contains hollocellulose (celluloses and hemicelluloses), lignin, remaining lipid and protein. This residue is a valuable resource for bioenergy production via thermochemical conversion (Kebelmann et al., 2013).

Recently, several studies on microalgae pyrolysis have been reported. Shuping et al. studied the pyrolysis characteristics and kinetics of the marine microalgae Dunaliella tertiolecta and reported that the activation energy of D. tertiolecta pyrolysis was 145.713 kJ/mol using Kissinger’s method and 146.421 kJ/mol by using Flynn–Wall–Ozawa’s method (Shuping et al., 2010). Similarly, Kim et al. found that the pyrolysis activation energy of the alga Saccharina Japonica was within 102.5–269.7 kJ/mol, depending on the pyrolysis conversion (Kim et al., 2012). In another work, the pyrolysis of two types of autotrophic microalgae, Spirulina Platensis and Chlorella Potothecoides, were examined by means of thermogravimetric analysis at different heating rates and the simple kinetic analysis adopting Freeman–Caroll method revealed the activation energy of 76–97 kJ/mol and 42–52 kJ/mol for S. Platensis and C. Potothecoides, respectively (Peng et al., 2001b). These values of activation energy are quite low for biomass pyrolysis. Liu at al. also investigated the pyrolysis of two types of microalgae Botryococcus braunii and Hapalosiphon sp. and their residues after partial oil extraction (Liu et al., 2012). The result revealed that the pyrolysis characteristic of both original microalgae and residual biomass after oil extraction was similar. Noticeably, the pyrolysis activation energy of as low as 5.5 kJ/mol was reported for the residue of Hapalosiphon sp. These significant variations in the kinetic data indicate limitations of the single reaction model assumptions.

In the open literature, there were no reports available for kinetic study on pyrolysis of microalgae or microalgae residue applying pseudo-component models, despite the fact that lignocellulosic material is the main component of the microalgae cell wall and the pyrolysis of such complex material cannot be closely described by the simple models. Therefore, the work reported in this paper was carried out to perform a kinetic analysis for the pyrolysis of microalgae residues adopting the pseudo-components model.

Section snippets

Material and experimental methods

All samples of microalgae residues used in this study were characterized and obtained from the previous work (Chen et al., 2014a, Su et al., 2007). Two species of microalgae, Chlamydomonas sp. JSC4 (C. sp. JSC4) and Chlorella sorokiniana CY1 (C. sorokiniana CY1) were collected from Southern Taiwan. The lipid oils were then extracted by the direct transesterification method (Su et al., 2007).

In the process of oil extraction, the microalgae cells separated by centrifugation (10,000 rpm) were

Thermogravimetrical characterization of microalgae residues

Fig. 1 presents the mass loss in the form of raw data (TGA) curves and the mass loss rate in the derivative form (DTG) curves of the microalgae residues during the pyrolysis process in the range temperature from 300 K to 1000 K. In general, the pyrolysis process can be divided into three different stages. The first stage was taking place from the initial temperature to 473 K approximately. The mass loss of each sample within this stage was small, about 4%, mainly contributed by the intrinsic

Conclusion

The assumed five pseudo-components model has been proven suitable to simulate the pyrolysis of microalgae residues. The extracted kinetic data are within the reasonable range in comparison with the literatures. For both cases of n = 1 and n # 1, there was no significant difference in the obtained kinetic data. The results from the case of n # 1 are however slightly better than that of n = 1 with regards to the fit quality. Small differences between the simulations for n = 1 and n # 1 in term of

Acknowledgements

The authors would like to thank Prof. Jo-Shu Chang, at Department of Chemical Engineering – National Cheng Kung University, for providing the microalgae residues used in this study.

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