Elsevier

Computers & Chemical Engineering

Volume 60, 10 January 2014, Pages 231-241
Computers & Chemical Engineering

A phenomenological model of the mechanisms of lignocellulosic biomass pyrolysis processes

https://doi.org/10.1016/j.compchemeng.2013.09.008Get rights and content

Highlights

  • A comprehensive fundamental model for studying biomass pyrolysis was developed.

  • Effect of particle size and temperature on biomass conversion was examined.

  • Effect of moisture content and particle shrinkage on pyrolysis rate was analyzed.

Abstract

A comprehensive particle scale model for pyrolysis of biomass has been developed by coupling the reaction mechanisms and transport phenomena. The model, which also accounts for the combined effect of various parameters such as particle shrinkage and drying, was validated using available experimental data from the literature. The validated model was then used to study the effect of operating temperature and biomass particle size, both of which strongly influenced the rate of biomass conversion. For example, for particle sizes less than 1 mm, a uniform temperature throughout the particle was predicted, thus leading to higher conversion rates in comparison to those in the larger particles. On the other hand, any increase in moisture content led to considerable decrease in the rate of biomass conversion. For the operating conditions considered in this study, the volumetric particle shrinkage also increased the decomposition of biomass to end products.

Introduction

Owing to their possible effect on the global warming, there is a worldwide drive to reduce our reliance on fossil fuels, which contribute about 98% of carbon emissions (Demirbaş, 2006). Also, there is a shift from non-renewable energy sources to bio-energy (bio-fuels) due to continuous depletion of fossil fuels. Biofuels are derived from biomass, which significantly decreases emissions of harmful gases such as SOx and NOx (Zhang, Chang, Wang, & Xu, 2007). Examples of commonly used biomass include plant matter such as forest residues (dead trees, branches and tree stumps), yard clippings, wood chips and municipal solid waste. The benefit of using biomass arises due to its renewable nature and ability to re-utilize the emitted greenhouse gas (CO2). Biomass-derived fuels are currently estimated to contribute around 13% of the world's energy supply (Demirbas, Balat, & Balat, 2009). Pyrolysis is one of several processes for producing energy from biomass (Chakravarti, Bonaquist, Drnevich, & Shah, 2012), where a set of thermo-chemical decomposition processes are used to convert the organic materials in biomass into carbon-rich solid and volatile matters by heating in the absence of oxygen (Demirbas & Arin, 2002). The solid content of pyrolysis products is known as the biochar or char, and is generally high in carbon content. The volatile contents are partly condensed to give a liquid fraction called tar or bio-oil (high molecular weight compounds) along with a mixture of the non-condensable gases (H2, CO, CO2, and C1–C4 hydrocarbons). The formation of these products is from both primary decomposition of the solid biomass as well as secondary reactions of condensable volatile organic products into low-molecular weight gases, secondary tar and char, while transporting through particle and reactor gas environment (Di Blasi, 2008). The proportion in which liquid and solid products are formed is dictated by not only feedstock properties but also the operating conditions.

Due to the increasing applications of biomass pyrolysis for value added products formation, several modelling studies have been reported in the literature. Thurner and Mann (1981) developed a model for investigating the kinetics of gas, char and tar formation from the pyrolysis of wood. Di Blasi and Branca (2001) examined the kinetics of isothermal primary degradation of beech wood in temperature range of 300–435 °C. They (Di Blasi & Branca, 2001) found that variation in the product yields and kinetic rates was mainly because of the effect of different heating rates, operating temperatures and experimental setups. Liden, Berruti, and Scott (1988) proposed a kinetic model for production of organic liquids from flash pyrolysis of biomass. In their model, it was assumed that wood or other biomass decomposes according to two parallel reactions yielding gas with char, and liquid tar which further decomposes by secondary homogeneous reactions into gaseous products. Some more studies had been undertaken for analysing the secondary tar cracking reactions during biomass pyrolysis (Baumlin et al., 2005, Boroson et al., 1989b, Fagbemi et al., 2001, Font et al., 1990, Morf et al., 2002).

For studying the dynamics of pyrolysis process, different models (Chan et al., 1985, Di Blasi, 1993b, Kansa et al., 1977, Koufopanos et al., 1991) had been proposed for understanding transport phenomena with chemical kinetics inside biomass particle. Di Blasi (1996) proposed a transport model for studying the effect of particle shrinkage on pyrolysis. Some assumptions such as negligible moisture content and no condensation of tar species inside the particle were also taken into account (Di Blasi, 1996). Bryden and Hagge (2003) analyzed the pyrolysis of a moist, shrinking biomass particle in their model. The authors combined the impact of moisture and particle shrinkage on pyrolysis times and product yields were taken into account. Although this model included the effect of shrinkage due to char, it ignored the shrinkage due to the volume occupied by volatiles (Di Blasi, 1996). Park, Atreya, and Baum (2010) studied the degradation mechanism of wood at different temperatures. In this model, the major emphasis was on the endo/exothermicity of the reactions occurring during the process, and also to the effect of pressure generation on particle structure. However, this model did not account for particle shrinkage and diffusive flux for gaseous species. Lu et al. (2010) proposed a model for studying the effect of particle shape and size on the rate of biomass devolatilization. They contradicted the results of Janse, Westerhout, and Prins (2000) by stating that spherical particles have slower rate of heat and mass transfer as compared to other aspherical particles of the same volume/mass. Recently, Peters (2011) developed a model for analysing the pyrolysis rate of different biomass samples such as spruce, beech, casuarina, pine wood, cellulose and lignin for different heating rates and particle geometries. However, these models (Lu et al., 2010, Peters, 2011) did not include the effect of particle shrinkage and drying during the pyrolysis.

Although there were currently several models for pyrolysis of biomass particles for predicting the rate of biomass degradation and product yields, most of these models cannot predict the combined effect of all the physical and chemical processes such as moisture content and particle shrinkage. Furthermore, any change in thermo-physical properties of biomass during pyrolysis and catalytic effect of biochar on tar cracking reactions has not been explicitly considered. In this study, a comprehensive model for pyrolysis of biomass particle has been developed, which not only considers the combined impact of process parameters but also includes the catalytic effect of biochar on reaction mechanism.

Section snippets

Model development

In order to develop a comprehensive model for the pyrolysis of biomass particles, kinetic models for both primary decomposition of biomass and secondary tar cracking reactions as well as momentum, mass and energy balances for biomass degradation were included in the model. Below we briefly describe development of this model under following sub-headings.

Numerical solution

The momentum, mass and heat balance equations were solved using PDE (partial differential equation) solver pdepe of MATLAB 7.0. This solves initial-boundary value problems for systems of parabolic and elliptic PDEs in the one space variable r and time t. The solver converts the PDEs to ODEs (ordinary differential equation) using a second-order accurate spatial discretization based on a specified grid size. The time integration of ODEs was completed using differential-algebraic equation solver

Results and discussion

The model results were validated using experimental data available in the literature. The effect of temperature, particle size, moisture content and shrinkage on biomass conversion in different operating conditions has been analyzed.

Validation of model results has been done using experimental studies of Sreekanth and Kolar (2009). The conversion time of a 10 mm diameter and 10 mm long wood particle (Casuarina equisetifolia) with about 10% moisture content was analyzed in a lab-scale fluidized bed

Conclusions

A detailed phenomenological model of thermo-chemical decomposition of biomass has been developed. The model includes the kinetics of both the primary solid phase and the secondary gaseous phase (tar) reactions on a lumped basis. The model predictions compared well with the available experimental results for the effect of operating temperature and particle size on the biomass conversion. The effect of the moisture content and particle shrinkage was further analyzed and it was found that both

Acknowledgement

This research has been partially supported by the Australian Research Council (ARC) under the ARC Linkage projects Scheme (Project # ARC LP100200135).

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