Thermal Analysis in Biomass Combustion: Comparison
Please note this is a comparison between Version 2 by Jessie Wu and Version 1 by João Pedro Silva.

Driven by its accessibility, extensive availability, and growing environmental consciousness, solid biomass has emerged as a viable alternative to enhance the diversity of renewable energy sources for electricity generation. To understand the phenomena involved in solid biomass conversion, it is necessary not only to understand the stages of the biomass combustion process but also to understand specifically the kinetics of the reaction and the release of the volatiles.

  • biomass
  • combustion
  • kinetics
  • macro thermogravimetric analysis

1. Introduction

Energy demand has increased over the years due to population growth and industrial and socio-economic developments, cornerstones of human civilization. As fossil fuels have been the backbone of energy supply worldwide, they are linked with climate change and global warming. Besides the protection of the environment, the depletion of fossil fuel resources is an important aspect that needs to be overcome. Consequently, using alternative energy sources to reduce environmental problems and strain on limited supply is currently a primary concern. As an alternative clean energy source, biomass appears to be a very interesting option as it is considered a sustainable, renewable, and CO2-neutral energy source [1], even though this has been seriously debated recently [2,3,4,5,6][2][3][4][5][6]. Furthermore, its abundance and availability not depending on weather conditions make this resource an attractive and valuable alternative for energy supply in both domestic and industrial sectors. Banja et al. [7] noted that biomass is the main contributor to EU renewable energy markets and due to its lower carbon footprint, has a significant contribution to low-carbon economy which results in its key role within the EU policy in the support for renewable energy sources. Furthermore, the International Energy Agency Roadmap—Net Zero Emissions by 2050—identifies bioenergy as an important source of energy, projected to represent 18% of the total energy supply in 2050,playing a key role in the transition toward a carbon-neutral society [8]. This number considers the direct replacement of fossil fuels and, indirectly, the counterbalance emissions by coupling the use of bioenergy with carbon capture and storage. In 2019, the replacement of fossil fuels with biomass avoided 290 MtCO2eq emissions, equivalent to approximately 8% of the EU27 GHG emissions [9].
Nowadays, biomass thermochemical conversion can be categorized into several main types, including combustion, pyrolysis, gasification, and hydrothermal processes. These processes have gained significant interest in recent years due to their potential to produce renewable energy and/or bio-based products while reducing greenhouse gas emissions. Each one has different characteristics and results in different products [10], combustion being the oldest and most mature technology for the production of heat and power. Additionally, the main route for providing renewable heat is solid biomass combustion, typically in grate-fired boilers. The applications of biomass combustion cover a wide range from domestic equipment with dozens of kW to district heating, dedicated, or combined heat and power plants with up to hundreds of MW of installed capacity. The successive climate targets for 2020, 2030, and 2050 have progressively reduced gas emissions targets up to 80% by increasing the share of renewable energy in the energy mix [11]. Nonetheless, there are countries like Portugal, with regard to the biomass sector, that only promote the development of new small co-generation biomass plants (up to 15 MW [12]). The low efficiency of dedicated large-scale biomass plants certainly discourages support for them.
The low efficiency is related to the complexity of the biomass combustion process, its instability, and the non-utilization of the available thermal energy for other purposes. Biomass combustion involves simultaneous multiphase fluid flow, chemical reactions, heat (convection and radiation), and mass transfer [13]. Due to this complex and irregular process, there are various operational problems inside an industrial boiler. Additionally, the pollutant emission limit is often exceeded.
In this regard, in order to give scientific insight into this phenomenon, experiments and Computational Fluid Dynamics (CFD) modeling are complementary tools for the development of thermal analysis, in-depth study of each reaction, and prediction of the gas flow to further anticipate problems that can occur during the combustion phase. The understanding of the processes in the fuel bed is rather limited, as it is difficult to obtain information through direct measurements because of the limited physical and optical accessibility inside a grate-fired boiler. 

2. Thermal Analysis in Biomass Combustion

As it is impossible to maintain repeatable and fully controlled conditions, and to monitor all the dynamics involved in lab-scale experiments, it becomes necessary to perform investigations at a small scale. This should be adequate to provide a controlled environment, and large enough to define realistic conditions. Furthermore, due to the design and operation of industrial biomass boilers, there is a need to model the combustion to further determine their key operating and design parameters. Moreover, biomass combustion in grate-fired boilers can be described as a series of reactions, which begins at a relatively small scale.
As represented in Figure 1, a comprehensive understanding of devolatilization is fundamental to the conversion process. In order to completely characterize this stage, the kinetics of the reaction and the determination of the volatiles released are essential. The study of biomass combustion behavior and the kinetics of the solid-state reactions have been developed through fundamental thermal analysis methods. According to the International Confederation for Thermal Analysis and Calorimetry (ICTAC), thermal analysis is referred to as a group of techniques where a property of the sample is monitored against time and/or temperature and, consequently, the change of the sample in terms of its weight is measured as a result of an imposed temperature profile in a specified atmosphere [14]. In previous work, thermogravimetric analysis (TGA) is the most common thermoanalytical technique used for solid-phase thermal degradation studies and for kinetic measurements [15[15][16],16], while analysis of the gaseous release process and the heat and mass transfer effects can be evaluated using the same technique but at a larger scale, which is commonly known as macro-TGA [17].
Figure 1.
An overview of the phenomena occurring during the multi-scale biomass combustion process.

2.1. Thermogravimetric Analysis

As biomass combustion is a complex process [18], it is important to understand the physical and chemical processes involved at the particle level to enable proper understanding [19,20][19][20]. TGA is a powerful tool used to study the devolatilization rate during the biomass combustion process and obtain important parameters which are essential in characterizing and understanding its behavior [21,22][21][22]. TGA is widely implemented for investigating and comparing thermal degradation events and kinetics during the combustion of solid materials such as coal and biomass [23]. The decrease in mass is measured under controlled conditions while the thermal process is taking place, as the temperature increases with time. Consequently, information about the thermal conversion dependency on temperature will be obtained at the particle scale. According to the search results from the Web of Science Database using the keywords “thermogravimetric analysis” and “biomass”, there has been a growing trend around biomass and the application of TGA to biomass in scientific journals since 2000. Figure 2 presents the annual number of publications from 2000 to 2021, which highlights the use and importance of TGA to investigate the thermal decomposition of biomass.
Figure 2. Number of annual publications from 2000 to the present on thermogravimetric analysis, TGA, and biomass: Data Source: results from Web of Knowledge Database.
A thermogravimetric analyzer consists of a sample pan that is supported by a precision balance placed in a furnace where the heating rate and environment can be controlled. Time, temperature, and weight are the three variables continuously measured and recorded during the TGA experiment. Taking the first derivative of such recorded data, known as derivative thermogravimetry (DTG), important parameters of thermal behavior characterization are provided. These key parameters are initial decomposition (Tin), peak (Tmax), and burnout (Tb) temperatures. Tin corresponds to the beginning of the weight loss, and it is defined as the temperature at which the rate of weight loss reaches 1%/min after the initial moisture loss peak in the DTG profile. Tmax is the point at which the maximum reaction rate occurs. Tb is identified when the last peak comes to the end and the temperature at which the sample is completely oxidized. It is taken as the point immediately before the reaction ceases when the rate of weight loss is down to 1%/min [24]. All this information allows for the thermal decomposition characterization of biomass samples and, in particular, the last two characteristic temperatures are important fuel parameters, especially in establishing the residence time in the combustion chamber. The experimental procedure and the most important points are illustrated in Figure 3.
Figure 3.
Mass loss as a function of time (above) and temperature (below) during the combustion of biomass [25].
The shape of the thermogravimetric curves (TG) and DTG curves is dependent on several factors, including the type of biomass; atmosphere and its flow rate; the heating program which includes the heating rate and the final temperature; initial mass; and the particle size of the fuel [26]. These constitute the main factors that affect the TG and that will determine the characteristic thermal decomposition behavior. The initial mass and particle size should be as small as possible to avoid the effect of heat and mass transfer limitations [11,27][11][27]. Regarding the atmosphere, there are two options to be considered: the oxidative or inert. An oxidative atmosphere greatly affects the devolatilization behavior [28]. The final temperature must be high enough for the complete decomposition of the carbonaceous materials. Finally, the heating rate is an important parameter as it greatly affects the rate of release of the volatiles due to the thermal inertia of the particles, and, in this way, different heating rates should be applied in order to study its influence [29].
Non-isothermal experiments are generally adopted for the determination of kinetic parameters as they are considered more reliable and less time-consuming when compared with isothermal experiments [30]. Moreover, TGA is very useful in studying the kinetics of biomass combustion because it is a simple and effective way to obtain information on the processes taking place for determining the kinetic parameters [31,32,33,34][31][32][33][34]. Thus, non-isothermal experiments include information on the temperature dependence of the reaction rate, and it is commonly believed that this would be sufficient to derive Arrhenius parameters and the reaction model of a process [35]. Consequently, the heating rate is one of the most relevant parameters in TGA as it affects thermal decomposition and, usually, experiments need to be performed with different heating rates to resolve possible compensation effects [36]. Thus, the Kinetics Committee of the ICTAC recommends that no less than three different temperature programs should be applied to obtain quality kinetic data [37].
The TGA results depend on several factors, but studies with a low heating rate are better at determining more precisely the temperatures from which the pyrolytic reactions start and avoiding transport effects [38]. In addition to the influence of the temperature and heating rate, Williams et al. [39] showed that the composition of the final products is dependent on the atmosphere. According to Vamvuka et al. [40], decreasing the oxygen concentration and increasing the particle size and moisture content will cause the ignition and burnout temperature to increase. Consequently, these variations will increase the residence time in the combustion chamber. Furthermore, Vamvuka et al. [40] reported that the composition of the gases, tars, and chars derived from biomass combustion depends on the heating rate and final temperature amongst other factors. Mani et al. [41] also investigated the influence of different parameters and found that the curves corresponding to the third stage of pyrolysis depend upon the particle size, initial weight, and heating rate of the pyrolysis process. Furthermore, an increase in the particle size and heating rate increases the char yield at the end of the experiments. Boriouchkine et al. [42] investigated the combustion of different particle sizes of spruce bark and wood residues. This restudy earch revealed that larger particles produced the highest maximum mass-loss rate when compared to smaller particles. Regarding the effect of the heating rate, Yorulmaz et al. [43] analyzed the combustion kinetics of treated and untreated waste wood using TGA under three different heating rates. This restudyearch revealed that by increasing the heating rate, the peak and burnout temperatures for all the samples were also increased, and higher temperatures were detected for the same weight loss. Shen et al. [44] examined the effect of the heating rate of four different biomass species, and the experimental results were used to develop a two-step reaction kinetic scheme with the activation energy depending on the heating rate. There have also been some studies that analyzed the effect of different heating rates on biomass decomposition under inert atmospheres [30,45,46,47,48,49,50][30][45][46][47][48][49][50]. However, as reported by Shen et al. [51] and Anca-Couce et al. [52], the presence of oxygen enhances biomass decomposition and promotes char combustion. Furthermore, the kinetic parameters derived from oxidant environments differ remarkably from experiments in the absence of oxygen [53].
Furthermore, in a real application of biomass combustion to produce power, for instance in an industrial grate-fired boiler, the temperature of the biomass increases and volatiles are quickly released due to the high heating rate that they are exposed to (around 1 to 100 K/s) [54]. This fast reaction results in insufficient air diffusing into the biomass, and ambient oxygen concentration varies over time which means that the reaction will change from pyrolysis to combustion [55]. Although modern boilers operate with oxygen-limited combustion under a low primary air flow rate, it is important to point out that most of the time this equipment operates with reaction-limited combustion due to a high primary air supply [56]. However, most of the studies in the literature have investigated pyrolysis using inert atmospheres [40,44,46,47,57,58,59,60,61,62,63,64][40][44][46][47][57][58][59][60][61][62][63][64].This is due to the fact that pyrolysis is the first step in thermochemical processes such as combustion and gasification [64].
Few results have been generated from experiments with air [36,43,44,65,66,67,68][36][43][44][65][66][67][68]. Shen et al. [51] and Anca-Couce et al. [52] reported that the presence of oxygen enhances biomass decomposition and promotes char combustion. Furthermore, the kinetic parameters resulting from oxidative atmospheres differ significantly from those in experiments conducted in the absence of oxygen [52]. Therefore, to simulate combustion conditions, it is important to study thermal behavior and kinetics in an oxygen atmosphere. Thus, in order to understand these differences, the influence of both oxidative and non-oxidative atmospheres on biomass thermal conversion have been studied by different authors [24,51,69,70][24][51][69][70]. Munir et al. [69] analyze the thermal characteristics of four waste biomass materials and the results showed that it is a complex phenomenon due to different microstructural and elemental characteristics as well as the type of atmosphere. The authors found that the weight loss rate in an inert atmosphere was slower, and its reactivity was 52% to 77% less than in oxidative conditions. Similar results were reported more recently by Sher et al. [70] who assessed the thermal and kinetic behaviors of diverse biomass fuels to provide valuable information for the power generation industry.
Yuzbasi et al. [24] compared the pyrolysis and combustion of co-firing biomass and coal with the individual behavior of each solid fuel. Regarding pyrolysis, a similar trend was obtained up to 700 °C. Furthermore, the oxygen levels shift the combustion profile to lower temperatures and increase the weight loss rate.
Shen et al. [51] investigated the thermal degradation of pine and birch and applied a new kinetic model, the distributed activation energy model (DAEM). DAEM was found unsuitable to describe the thermal decomposition of biomass under oxidant conditions due to the capacity of oxygen to accelerate the mass loss in the first stage and promote complex reactions in the second stage. Furthermore, some works analyzed the influence of oxidant and non-oxidant environments through experiments with different oxygen concentrations [28,55,71,72,73][28][55][71][72][73].
Fang et al. [55] studied the effects of oxygen concentration on the mass-loss rate and kinetics of pyrolysis and combustion of wood. The author stated that the mass-loss rates of wood were independent of oxygen concentration when the temperature was below 250 °C. Furthermore, it was found that the activation energy varied linearly with oxygen concentration at the first stage. Moreno et al. [73] also studied the kinetics of wood wastes and solid wood under different conditions examining three or four reactions with regards to whether the reaction occurred under oxidative or non-oxidative conditions. In turn, Amutio et al. [72] proposed a kinetic model consisting of six simultaneous reactions.
Chouchene et al. [71] studied the effect of three atmospheres with different oxygen content on the thermal degradation of solid waste. It was verified that pyrolysis under inert conditions takes place according to two different stages (drying and devolatilization) while under oxidative conditions a third stage, char oxidation, occurs. On the other hand, Su et al. [28] analyzed the effect of oxygen content on the thermal degradation of pine and similar results were obtained. The oxygen promoted the degradation of biomass, and a third stage was observed.
While the previous literature has cast light on TGA under a variety of conditions, only a few works have succeeded in analyzing thermal conversion, and determining all the kinetic parameters of experiments covering the possibility of oxidative and non-oxidative conditions with different flow rates. To date, several studies have considered these different parameters, including particle size [40,41,42][40][41][42] and heating rate [30[30][36][43][44][45][46][47][48][49][50][51][52][74][75][76][77][78][79][80],36,43,44,45,46,47,48,49,50,51,52,74,75,76,77,78,79,80], while studying their influence on thermal degradation behavior and kinetics. Additionally, in the literature, there are several kinetic data derived from the weight loss curves of biomass fuels in inert [29,41,42,46,47,48,50,60,61,62,79,81,82,83,84,85,86][29][41][42][46][47][48][50][60][61][62][79][81][82][83][84][85][86] and air [27,36,43,66,67,87,88,89][27][36][43][66][67][87][88][89] atmospheres. There are also other investigations that have studied the influence of the atmosphere and applied both atmospheres [24,28,51,55,69,70,73][24][28][51][55][69][70][73]. This extensive literature review concludes with the selection and analysis of works that analyzed the most representative solid biomass fuels (eucalyptus, acacia, and pine), which are summarized in Table 1.
Hence, considering the current state-of-the-art in this subject, many factors can affect the kinetic parameters, including not only the process conditions, heterogeneity of the sample, heat and mass transfer limitations, and systematic errors, but also the processing and method for the analysis of the TGA results [16]. Consequently, a wide range of kinetic parameters has been reported in the literature and, therefore, direct comparisons are not possible. As evidence of this inconsistency, Figure 4 presents the different activation energy values reported in the literature for pine devolatilization and char oxidation. The set of results show a wide dispersion of data, which can be by a factor of up to five, depending on the author. This clearly shows that further experimentation should be carried out using TG analysis for the determination of the activation energy at each step of the biomass conversion.
Figure 4. Activation energy values reported in the literature for pine devolatilization and char oxidation using two-step sequential models. The red bars are results considering a global reaction. Data Source: [43,44,51,72,74,90,91,96,99][43][44][51][72][74][90][91][96][99].

2.2. Macro Thermogravimetric Analysis

Experiments in a lab-scale reactor are an interesting alternative to address the biomass conversion in a real scale, and also to provide complementary knowledge to the TGA results about the kinetics of the reaction in the thermal biomass decomposition. This is also particularly interesting because the conditions in biomass industrial boilers are different, and it is important to investigate the thermal decomposition of larger particles and higher biomass quantities than those possible with TGA experiments. This possibility will allow uresearchers to take into consideration the heat and mass diffusion in the reaction mechanism. Furthermore, using larger samples, the effects of secondary reactions together with the possibility of operating at higher heating rates can also affect the reaction kinetics. Consequently, due to the complexity of the combustion process inside industrial boilers, which is enhanced with the motion of the fuel bed, there are several authors that report experiments in a batch reactor in order to describe the entire process in a traveling or vibrating grate boiler [100,101,102,103,104,105][100][101][102][103][104][105]. These experiments often include the combustion of a large amount of biomass (in the range of a number of kilograms). Experiments using batch reactors are also performed to quantify the implications of differences in fuel properties, and to investigate the propagation of a combustion front, i.e., the drying, pyrolysis, and char combustion process, in a bed of biomass particles. Such experiments are useful to develop parametric studies with different operating conditions (primary and secondary air flow rate and temperature) and different fuel properties (moisture content, volatile matter, ash content, chemical composition, heating values, and particle size). The ignition front velocity, ignition rate, conversion rate, and temperature of the reaction zone are the parameters most commonly obtained to evaluate combustion behavior.

References

  1. Saidur, R.; Abdelaziz, E.A.; Demirbas, A.; Hossain, M.S.; Mekhilef, S. A review on biomass as a fuel for boilers. Renew. Sustain. Energy Rev. 2011, 15, 2262–2289.
  2. Norton, M.; Baldi, A.; Buda, V.; Carli, B.; Cudlin, P.; Jones, M.B.; Korhola, A.; Michalski, R.; Novo, F.; Oszlányi, J.; et al. Serious mismatches continue between science and policy in forest bioenergy. GCB Bioenergy 2019, 11, 1256–1263.
  3. Bilgili, F.; Koçak, E.; Bulut, Ü.; Kuşkaya, S. Can biomass energy be an efficient policy tool for sustainable development? Renew. Sustain. Energy Rev. 2017, 71, 830–845.
  4. Cowie, A.; Cowie, A.; Junginger, M.; Ximenes, F. Response to Chatham House Report “Woody Biomass for Power and Heat: Impacts on the Global Climate”. 2017, pp. 1–14. Available online: https://www.ieabioenergy.com/wp-content/uploads/2017/03/Chatham_House_response_supporting-doc.pdf (accessed on 16 September 2022).
  5. Gustavsson, L.; Haus, S.; Ortiz, C.A.; Sathre, R.; Le Truong, N. Climate effects of bioenergy from forest residues in comparison to fossil energy. Appl. Energy 2015, 138, 36–50.
  6. Evans, A.; Strezov, V.; Evans, T.J. Sustainability considerations for electricity generation from biomass. Renew. Sustain. Energy Rev. 2010, 14, 1419–1427.
  7. Banja, M.; Sikkema, R.; Jégard, M.; Motola, V.; Dallemand, J.-F. Biomass for energy in the EU—The support framework. Energy Policy 2019, 131, 215–228.
  8. IEA. Net Zero by 2050—A Roadmap for the Global Energy Sector. 2021. Available online: https://iea.blob.core.windows.net/assets/deebef5d-0c34-4539-9d0c-10b13d840027/NetZeroby2050-ARoadmapfortheGlobalEnergySector_CORR.pdf (accessed on 16 September 2022).
  9. Deloitte. Towards an Integrated Energy System: Assessing Bioenergy’s Socio-Economic and Environmental Impact. 2022. Available online: https://bioenergyeurope.org/article/347-towards-an-integrated-energy-system-assessing-bioenergy-s-socio-economic-and-environmental-impact.html (accessed on 16 September 2022).
  10. Goyal, H.; Seal, D.; Saxena, R. Bio-fuels from thermochemical conversion of renewable resources: A review. Renew. Sustain. Energy Rev. 2008, 12, 504–517.
  11. Di Blasi, C.; Branca, C.; Santoro, A.; Gonzalez Hernandez, E. Pyrolytic behavior and products of some wood varieties. Combust. Flame 2001, 124, 165–177.
  12. Gil, L.; Bernardo, J. An approach to energy and climate issues aiming at carbon neutrality. Renew. Energy Focus 2020, 33, 37–42.
  13. Nussbaumer, T. Combustion and Co-combustion of Biomass: Fundamentals, Technologies, and Primary Measures for Emission Reduction. Energy Fuels 2003, 17, 1510–1521.
  14. Richardson, M.J. Thermal Analysis. In Comprehensive Polymer Science and Supplements; Elsevier: Amsterdam, The Netherlands, 1989; pp. 867–901.
  15. Vyazovkin, S.; Chrissafis, K.; Di Lorenzo, M.L.; Koga, N.; Pijolat, M.; Roduit, B.; Sbirrazzuoli, N.; Suñol, J.J. ICTAC Kinetics Committee recommendations for collecting experimental thermal analysis data for kinetic computations. Thermochim. Acta 2014, 590, 1–23.
  16. White, J.E.; Catallo, W.J.; Legendre, B.L. Biomass pyrolysis kinetics: A comparative critical review with relevant agricultural residue case studies. J. Anal. Appl. Pyrolysis 2011, 91, 1–33.
  17. Fernandez, A.; Soria, J.; Rodriguez, R.; Baeyens, J.; Mazza, G. Macro-TGA steam-assisted gasification of lignocellulosic wastes. J. Environ. Manag. 2019, 233, 626–635.
  18. Williams, A.; Jones, J.; Ma, L.; Pourkashanian, M. Pollutants from the combustion of solid biomass fuels. Prog. Energy Combust. Sci. 2012, 38, 113–137.
  19. Silva, J.; Teixeira, J.; Teixeira, S.; Preziati, S.; Cassiano, J. CFD Modeling of Combustion in Biomass Furnace. In Energy Procedia; Elsevier: Amsterdam, The Netherlands, 2017; pp. 665–672.
  20. Silva, J.; Fraga, L.; Ferreira, M.E.; Chapela, S.; Porteiro, J.; Teixeira, S.F.C.F.; Teixeira, J. Combustion Modelling of a 20 kW Pellet Boiler. In Volume 6B Energy; American Society of Mechanical Engineers: New York, NY, USA, 2018; p. V06BT08A036.
  21. Biagini, E.; Guerrini, L.; Nicolella, C. Development of a variable activation energy model for biomass devolatilization. Energy Fuels 2009, 23, 3300–3306.
  22. Fraga, L.; Silva, J.; Soares, D.F.; Ferreira, M.; Teixeira, S.F.; Teixeira, J.C. Study of Devolatilization Rates of Pine Wood and Mass Loss of Wood Pellets. In ASME 2017 International Mechanical Engineering Congress and Exposition Volume 6 Energy; ASME: Tampa, FL, USA, 2017; p. 9.
  23. Gil, M.; Casal, D.; Pevida, C.; Pis, J.; Rubiera, F. Thermal behaviour and kinetics of coal/biomass blends during co-combustion. Bioresour. Technol. 2010, 101, 5601–5608.
  24. Yuzbasi, N.S.; Selçuk, N. Air and oxy-fuel combustion characteristics of biomass/lignite blends in TGA-FTIR. Fuel Process. Technol. 2011, 92, 1101–1108.
  25. Fraga, L.G.; Silva, J.; Teixeira, J.C.F.; Ferreira, M.E.C.; Soares, D.F.; Teixeira, S.F. The effect of the heating and air flow rate on the mass loss of pine wood particles. In Proceedings of the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, Guimarães, Portugal, 17–22 June 2018.
  26. Jenkins, B.M.; Baxter, L.L.; Miles, T.R., Jr.; Miles, T.R. Combustion properties of biomass. Fuel Process. Technol. 1998, 54, 17–46.
  27. Magalhães, D.; Kazanç, F.; Riaza, J.; Erensoy, S.; Kabaklı; Chalmers, H. Combustion of Turkish lignites and olive residue: Experiments and kinetic modelling. Fuel 2017, 203, 868–876.
  28. Su, Y.; Luo, Y.; Wu, W.; Zhang, Y.; Zhao, S. Characteristics of pine wood oxidative pyrolysis: Degradation behavior, carbon oxide production and heat properties. J. Anal. Appl. Pyrolysis 2012, 98, 137–143.
  29. Saeed, M.; Andrews, G.; Phylaktou, H.; Gibbs, B. Global kinetics of the rate of volatile release from biomasses in comparison to coal. Fuel 2016, 181, 347–357.
  30. Mishra, R.K.; Mohanty, K. Pyrolysis kinetics and thermal behavior of waste sawdust biomass using thermogravimetric analysis. Bioresour. Technol. 2018, 251, 63–74.
  31. Skreiberg, A.; Skreiberg; Sandquist, J.; Sørum, L. TGA and macro-TGA characterisation of biomass fuels and fuel mixtures. Fuel 2011, 90, 2182–2197.
  32. Magdziarz, A.; Wilk, M. Thermogravimetric study of biomass, sewage sludge and coal combustion. Energy Convers. Manag. 2013, 75, 425–430.
  33. Grammelis, P.; Basinas, P.; Malliopoulou, A.; Sakellaropoulos, G. Pyrolysis kinetics and combustion characteristics of waste recovered fuels. Fuel 2009, 88, 195–205.
  34. Biswas, S.; Choudhury, N.; Sarkar, P.; Mukherjee, A.; Sahu, S.; Boral, P.; Choudhury, A. Studies on the combustion behaviour of blends of Indian coals by TGA and Drop Tube Furnace. Fuel Process. Technol. 2006, 87, 191–199.
  35. Vyazovkin, S.; Wight, C.A. Isothermal and non-isothermal kinetics of thermally stimulated reactions of solids. Int. Rev. Phys. Chem. 1998, 17, 407–433.
  36. Garcia-Maraver, A.; Perez-Jimenez, J.A.; Serrano-Bernardo, F.; Zamorano, M. Determination and comparison of combustion kinetics parameters of agricultural biomass from olive trees. Renew. Energy 2015, 83, 897–904.
  37. Vyazovkin, S.; Burnham, A.K.; Criado, J.M.; Pérez-Maqueda, L.A.; Popescu, C.; Sbirrazzuoli, N. ICTAC Kinetics Committee recommendations for performing kinetic computations on thermal analysis data. Thermochim. Acta 2011, 520, 1–19.
  38. Anca-Couce, A.; Tsekos, C.; Retschitzegger, S.; Zimbardi, F.; Funke, A.; Banks, S.; Kraia, T.; Marques, P.; Scharler, R.; de Jong, W.; et al. Biomass pyrolysis TGA assessment with an international round robin. Fuel 2020, 276, 118002.
  39. Williams, P.T.; Besler, S. The influence of temperature and heating rate on the slow pyrolysis of biomass. Renew. Energy 1996, 7, 233–250.
  40. Vamvuka, D.; Sfakiotakis, S. Combustion behaviour of biomass fuels and their blends with lignite. Thermochim. Acta 2011, 526, 192–199.
  41. Mani, T.; Murugan, P.; Abedi, J.; Mahinpey, N. Pyrolysis of wheat straw in a thermogravimetric analyzer: Effect of particle size and heating rate on devolatilization and estimation of global kinetics. Chem. Eng. Res. Des. 2010, 88, 952–958.
  42. Boriouchkine, A.; Sharifi, V.; Swithenbank, J.; Jämsä-Jounela, S.-L. A study on the dynamic combustion behavior of a biomass fuel bed. Fuel 2014, 135, 468–481.
  43. Yorulmaz, S.Y.; Atimtay, A.T. Investigation of combustion kinetics of treated and untreated waste wood samples with thermogravimetric analysis. Fuel Process. Technol. 2009, 90, 939–946.
  44. Shen, D.; Gu, S.; Luo, K.; Bridgwater, A.; Fang, M. Kinetic study on thermal decomposition of woods in oxidative environment. Fuel 2009, 88, 1024–1030.
  45. Kim, S.-S.; Kim, J.; Park, Y.-K. Pyrolysis kinetics and decomposition characteristics of pine trees. Bioresour. Technol. 2010, 101, 9797–9802.
  46. Seo, D.K.; Park, S.S.; Hwang, J.; Yu, T.-U. Study of the pyrolysis of biomass using thermo-gravimetric analysis (TGA) and concentration measurements of the evolved species. J. Anal. Appl. Pyrolysis 2010, 89, 66–73.
  47. Slopiecka, K.; Bartocci, P.; Fantozzi, F. Thermogravimetric analysis and kinetic study of poplar wood pyrolysis. Appl. Energy 2012, 97, 491–497.
  48. Chen, D.; Zheng, Y.; Zhu, X. In-depth investigation on the pyrolysis kinetics of raw biomass. Part I: Kinetic analysis for the drying and devolatilization stages. Bioresour. Technol. 2013, 131, 40–46.
  49. Mishra, G.; Kumar, J.; Bhaskar, T. Kinetic studies on the pyrolysis of pinewood. Bioresour. Technol. 2015, 182, 282–288.
  50. Wang, X.; Hu, M.; Hu, W.; Chen, Z.; Liu, S.; Hu, Z.; Xiao, B. Thermogravimetric kinetic study of agricultural residue biomass pyrolysis based on combined kinetics. Bioresour. Technol. 2016, 219, 510–520.
  51. Shen, D.; Gu, S.; Jin, B.; Fang, M. Thermal degradation mechanisms of wood under inert and oxidative environments using DAEM methods. Bioresour. Technol. 2011, 102, 2047–2052.
  52. Anca-Couce, A.; Zobel, N.; Berger, A.; Behrendt, F. Smouldering of pine wood: Kinetics and reaction heats. Combust. Flame 2012, 159, 1708–1719.
  53. Peters, B.; Raupenstrauch, H. Modeling Moving and Fixed Bed Combustion. In Handbook of Combustion; Wiley-VCH: Weinheim, Germany, 2010; p. 4.
  54. Kleinhans, U.; Wieland, C.; Frandsen, F.J.; Spliethoff, H. Ash formation and deposition in coal and biomass fired combustion systems: Progress and challenges in the field of ash particle sticking and rebound behavior. Prog. Energy Combust. Sci. 2018, 68, 65–168.
  55. Fang, M.; Shen, D.; Li, Y.; Yu, C.; Luo, Z.; Cen, K. Kinetic study on pyrolysis and combustion of wood under different oxygen concentrations by using TG-FTIR analysis. J. Anal. Appl. Pyrolysis 2006, 77, 22–27.
  56. Yin, C.; Rosendahl, L.A.; Kær, S.K. Grate-firing of biomass for heat and power production. Prog. Energy Combust. Sci. 2008, 34, 725–754.
  57. Xiao, R.; Yang, W.; Cong, X.; Dong, K.; Xu, J.; Wang, D.; Yang, X. Thermogravimetric analysis and reaction kinetics of lignocellulosic biomass pyrolysis. Energy 2020, 201, 117537.
  58. Flores, J.J.A.; Quiñones, J.G.R.; Rodríguez, M.L.; Vera, J.V.A.; Valencia, J.E.; Martínez, S.J.G.; Montesino, F.M.; Rosas, A.A. Thermal Degradation Kinetics and FT-IR Analysis on the Pyrolysis of Pinus pseudostrobus, Pinus leiophylla and Pinus montezumae as Forest Waste in Western Mexico. Energies 2020, 13, 969.
  59. Grønli, M.G.; Várhegyi, G.; Di Blasi, C. Thermogravimetric Analysis and Devolatilization Kinetics of Wood. Ind. Eng. Chem. Res. 2002, 41, 4201–4208.
  60. Saddawi, A.; Jones, J.M.; Williams, A.; Wójtowicz, M.A. Kinetics of the Thermal Decomposition of Biomass. Energy Fuels 2010, 24, 1274–1282.
  61. Darvell, L.; Jones, J.; Gudka, B.; Baxter, X.; Saddawi, A.; Williams, A.; Malmgren, A. Combustion properties of some power station biomass fuels. Fuel 2010, 89, 2881–2890.
  62. Parthasarathy, P.; Narayanan, K.S.; Arockiam, L. Study on kinetic parameters of different biomass samples using thermo-gravimetric analysis. Biomass Bioenergy 2013, 58, 58–66.
  63. Saldarriaga, J.F.; Aguado, R.; Pablos, A.; Amutio, M.; Olazar, M.; Bilbao, J. Fast characterization of biomass fuels by thermogravimetric analysis (TGA). Fuel 2015, 140, 744–751.
  64. Diblasi, C. Modeling chemical and physical processes of wood and biomass pyrolysis. Prog. Energy Combust. Sci. 2008, 34, 47–90.
  65. Bilbao, R.; Mastral, J.; Aldea, M.; Ceamanos, J. Kinetic study for the thermal decomposition of cellulose and pine sawdust in an air atmosphere. J. Anal. Appl. Pyrolysis 1997, 39, 53–64.
  66. Ren, X.; Chen, J.; Li, G.; Wang, Y.; Lang, X.; Fan, S. Thermal oxidative degradation kinetics of agricultural residues using distributed activation energy model and global kinetic model. Bioresour. Technol. 2018, 261, 403–411.
  67. Dhahak, A.; Bounaceur, R.; Le Dreff-Lorimier, C.; Schmidt, G.; Trouve, G.; Battin-Leclerc, F. Development of a detailed kinetic model for the combustion of biomass. Fuel 2019, 242, 756–774.
  68. Fraga, L.G.; Silva, J.; Teixeira, S.; Soares, D.; Ferreira, M.; Teixeira, J. Influence of Operating Conditions on the Thermal Behavior and Kinetics of Pine Wood Particles using Thermogravimetric Analysis. Energies 2020, 13, 2756.
  69. Munir, S.; Daood, S.; Nimmo, W.; Cunliffe, A.; Gibbs, B. Thermal analysis and devolatilization kinetics of cotton stalk, sugar cane bagasse and shea meal under nitrogen and air atmospheres. Bioresour. Technol. 2009, 100, 1413–1418.
  70. Sher, F.; Iqbal, S.Z.; Liu, H.; Imran, M.; Snape, C.E. Thermal and kinetic analysis of diverse biomass fuels under different reaction environment: A way forward to renewable energy sources. Energy Convers. Manag. 2020, 203, 112266.
  71. Chouchene, A.; Jeguirim, M.; Khiari, B.; Zagrouba, F.; Trouvé, G. Thermal degradation of olive solid waste: Influence of particle size and oxygen concentration. Resour. Conserv. Recycl. 2010, 54, 271–277.
  72. Amutio, M.; Lopez, G.; Aguado, R.; Artetxe, M.; Bilbao, J.; Olazar, M. Kinetic study of lignocellulosic biomass oxidative pyrolysis. Fuel 2012, 95, 305–311.
  73. Moreno, A.I.; Font, R.; Conesa, J.A. Combustion of furniture wood waste and solid wood: Kinetic study and evolution of pollutants. Fuel 2017, 192, 169–177.
  74. Álvarez, A.; Pizarro, C.; García, R.; Bueno, J.; Lavín, A. Determination of kinetic parameters for biomass combustion. Bioresour. Technol. 2016, 216, 36–43.
  75. Yu, D.; Chen, M.; Wei, Y.; Niu, S.; Xue, F. An assessment on co-combustion characteristics of Chinese lignite and eucalyptus bark with TG–MS technique. Powder Technol. 2016, 294, 463–471.
  76. Soria-Verdugo, A.; Goos, E.; García-Hernando, N. Effect of the number of TGA curves employed on the biomass pyrolysis kinetics results obtained using the Distributed Activation Energy Model. Fuel Process. Technol. 2015, 134, 360–371.
  77. Chen, Z.; Zhu, Q.; Wang, X.; Xiao, B.; Liu, S. Pyrolysis behaviors and kinetic studies on Eucalyptus residues using thermogravimetric analysis. Energy Convers. Manag. 2015, 105, 251–259.
  78. Soria-Verdugo, A.; Garcia-Gutierrez, L.; Blanco-Cano, L.; Garcia-Hernando, N.; Ruiz-Rivas, U. Evaluating the accuracy of the Distributed Activation Energy Model for biomass devolatilization curves obtained at high heating rates. Energy Convers. Manag. 2014, 86, 1045–1049.
  79. Kok, M.V.; Özgür, E. Thermal analysis and kinetics of biomass samples. Fuel Process. Technol. 2013, 106, 739–743.
  80. Granada, E.; Eguía, P.; Comesaña, J.A.; Patiño, D.; Porteiro, J.; Miguez, J.L. Devolatilization behaviour and pyrolysis kinetic modelling of Spanish biomass fuels. J. Therm. Anal. Calorim. 2013, 113, 569–578.
  81. Ghodke, P.; Mandapati, R.N. Investigation of particle level kinetic modeling for babul wood pyrolysis. Fuel 2019, 236, 1008–1017.
  82. Siddiqi, H.; Bal, M.; Kumari, U.; Meikap, B. In-depth physiochemical characterization and detailed thermo-kinetic study of biomass wastes to analyze its energy potential. Renew. Energy. 2019, 148, 756–771.
  83. Chen, J.; Wang, Y.; Lang, X.; Ren, X.; Fan, S. Evaluation of agricultural residues pyrolysis under non-isothermal conditions: Thermal behaviors, kinetics, and thermodynamics. Bioresour. Technol. 2017, 241, 340–348.
  84. Akinrinola, F.S.; Darvell, L.I.; Jones, J.M.; Williams, A.; Fuwape, J.A. Characterization of Selected Nigerian Biomass for Combustion and Pyrolysis Applications. Energy Fuels 2014, 28, 3821–3832.
  85. Amutio, M.; Lopez, G.; Alvarez, J.; Moreira, R.; Duarte, G.; Nunes, J.; Olazar, M.; Bilbao, J. Pyrolysis kinetics of forestry residues from the Portuguese Central Inland Region. Chem. Eng. Res. Des. 2013, 91, 2682–2690.
  86. Biagini, E.; Fantei, A.; Tognotti, L. Effect of the heating rate on the devolatilization of biomass residues. Thermochim. Acta 2008, 472, 55–63.
  87. Maia, A.A.D.; de Morais, L.C. Kinetic parameters of red pepper waste as biomass to solid biofuel. Bioresour. Technol. 2016, 204, 157–163.
  88. Aghamohammadi, N.; Sulaiman, N.M.N.; Aroua, M.K. Combustion characteristics of biomass in SouthEast Asia. Biomass Bioenergy 2011, 35, 3884–3890.
  89. Sanchez, M.; Otero, M.; Gómez, X.; Morán, A. Thermogravimetric kinetic analysis of the combustion of biowastes. Renew. Energy 2009, 34, 1622–1627.
  90. Xu, X.; Pan, R.; Chen, R. Combustion Characteristics, Kinetics, and Thermodynamics of Pine Wood Through Thermogravimetric Analysis. Appl. Biochem. Biotechnol. 2021, 193, 1427–1446.
  91. Chen, R.; Li, Q.; Xu, X.; Zhang, D.; Hao, R. Combustion characteristics, kinetics and thermodynamics of Pinus Sylvestris pine needle via non-isothermal thermogravimetry coupled with model-free and model-fitting methods. Case Stud. Therm. Eng. 2020, 22, 100756.
  92. Fu, S.; Chen, H.; Yang, J.; Yang, Z. Kinetics of thermal pyrolysis of Eucalyptus bark by using thermogravimetric-Fourier transform infrared spectrometry technique. J. Therm. Anal. Calorim. 2019, 139, 3527–3535.
  93. Vega, L.; López, L.; Valdés, C.F.; Chejne, F. Assessment of energy potential of wood industry wastes through thermochemical conversions. Waste Manag. 2019, 87, 108–118.
  94. Wadhwani, R.; Sutherland, D.; Moinuddin, K.A.M.; Joseph, P. Kinetics of pyrolysis of litter materials from pine and eucalyptus forests. J. Therm. Anal. Calorim. 2017, 130, 2035–2046.
  95. Cai, Z.; Ma, X.; Fang, S.; Yu, Z.; Lin, Y. Thermogravimetric analysis of the co-combustion of eucalyptus residues and paper mill sludge. Appl. Therm. Eng. 2016, 106, 938–943.
  96. Fang, X.; Jia, L.; Yin, L. A weighted average global process model based on two−stage kinetic scheme for biomass combustion. Biomass Bioenergy 2013, 48, 43–50.
  97. Lapuerta, M.; Hernández, J.J.; Rodríguez, J. Comparison between the kinetics of devolatilisation of forestry and agricultural wastes from the middle-south regions of Spain. Biomass Bioenergy 2007, 31, 13–19.
  98. Lapuerta, M.; Hernández, J.J.; Rodríguez, J. Kinetics of devolatilisation of forestry wastes from thermogravimetric analysis. Biomass Bioenergy 2004, 27, 385–391.
  99. Cancellieri, D.; Leroy-Cancellieri, V.; Silvani, X.; Morandini, F. New experimental diagnostics in combustion of forest fuels: Microscale appreciation for a macroscale approach. Nat. Hazards Earth Syst. Sci. 2018, 18, 1957–1968.
  100. Yang, Y.; Ryu, C.; Khor, A.; Sharifi, V.N.; Swithenbank, J. Fuel size effect on pinewood combustion in a packed bed. Fuel 2005, 84, 2026–2038.
  101. Ryu, C.; Yang, Y.B.; Khor, A.; Yates, N.E.; Sharifi, V.N.; Swithenbank, J. Effect of fuel properties on biomass combustion: Part I. Experiments—Fuel type, equivalence ratio and particle size. Fuel 2006, 85, 1039–1046.
  102. Mahmoudi, A.H.; Markovic, M.; Peters, B.; Brem, G. An experimental and numerical study of wood combustion in a fixed bed using Euler-Lagrange approach (XDEM). Fuel 2015, 150, 573–582.
  103. Wurzenberger, J.C.; Wallner, S.; Raupenstrauch, H.; Khinast, J.G. Thermal conversion of biomass: Comprehensive reactor and particle modeling. AIChE J. 2002, 48, 2398–2411.
  104. Markovic, M.; Bramer, E.A.; Brem, G. Experimental investigation of wood combustion in a fixed bed with hot air. Waste Manag. 2014, 34, 49–62.
  105. Erić, A.; Nemoda, S.; Komatina, M.; Dakić, D.; Repić, B. Experimental investigation on the kinetics of biomass combustion in vertical tube reactor. J. Energy Inst. 2019, 92, 1077–1090.
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