As briefly described in 1.17.3, one of the main sources of inaccuracies and difficulties experienced when modelling the emission behaviour of biomass thermal conversion processes is the lack of data and diversity of biomass (Solomon et al., 1991). There are only few accessible kinetic data available on the evolution of individual products during biomass pyrolysis (de Jong et al., 2003).
de Jong et al (2003) studied slow pyrolysis experiments for two types of biomass, namely pelletised Miscanthus Gigantheus and wood using TGA-FTIR. Samples were heated in helium at 10°C min-1. The temperature profile started with a drying period at 80°C for 20 min, followed by pyrolysis up to 900°C, at which was held for 3 min upon reaching the temperature and immediately cooled down to 250°C for 20 min. After cooling, oxygen was
added to the helium and the temperature was raised again to 900°C at 30°C min-1 to carry out the char combustion. This profile was repeated at pyrolysis heating rates of 30 and 100°C min-1. Concentrations of volatiles could be obtained from the infra-red spectrum based on calibration runs with pure compounds (which were not mentioned in the article), while yields of tar were determined by taking the differences using the sum of gases quantified by FTIR and the balance curve obtained by the TGA (de Jong et al., 2003). In this study, kinetic rates for species evolution were also determined and used as input files for (FG–DVC) biomass pyrolysis model.
The results showed that yields of condensables increased while those of CO2, CO and acetaldehyde (CH3CHO) decreased with increased heating rates. There were 12 other volatile species studied, that is methane (CH4), ethylene (C2H4), hydrogen cyanide (HCN), ammonia (NH3), isocyanic acid (HNCO), carbonyl sulphide (COS), sulphur dioxide (SO2), formaldehyde (CH2O), methanol (CH3OH), formic acid (HCOOH), acetic acid (CH3COOH), phenol (C6H5OH) and acetone (CH3OCH3).
With regards to FG-DVC model, it was originally developed by AFR to describe coal thermal decomposition by predicting the product distribution, extract yields, cross-link density, molecular weight distribution and fluidity as a function of coal rank, heating rate and pressure (de Jong et al., 2003). FG describes the gas evolution, compositions of the subject in terms of elemental and functional groups while DVC determines the amount and molecular weight of macromolecular fragments (de Jong et al., 2003). The DVC is de-emphasised when dealing with biomass because tar is treated just like any other volatile species in the biomass model. Figure 3.27 compares the evolution rates and yields of products from pyrolysis of wood between those obtained in TG-FTIR and those predicted by the FG-DVC model. It shows that the model correctly simulates the results for species such as water, methane, carbon dioxide and carbon monoxide while other species were difficult to fit with the experimental data.
Figure 3.27. Comparison between the results of TG-FTIR and FG-DVC model for evolution
rates and yields obtained from pyrolysis of wood pellets (de Jong et al., 2003).
3.12 Conclusions
Past literature reviews suggest that torrefaction is indeed a promising technique that can improve the performance of biomass fuels for future energy utilisation. This chapter highlights possible areas that require further research as there are noticeable gaps and remains of information that has not been studied in sufficient detail.
When this project began in the late 2010, most literatures focussed on the solid torrefied biomass. Standard characteristics of the torrefied fuel such as the colour, shape, size, moisture content, heating value and main elemental compositions were some of the common investigations that were carried out. Less attention was paid towards the change in its morphology composition and in depth look at its physical and chemical characteristics. Therefore, spectroscopic instruments, for example, Fourier Transform Infrared Spectroscopy and X-ray Photoelectron Spectroscopy and microscopies, namely, Scanning Electron Microscopy and Transmission Electron Microscopy as well as Brunauer-Emmett-Teller Surface Area Analysis were used thoroughly in this study.
Grindability behaviour of torrefied biomass in comparison to the untreated biomass was also of great interest in this project. The performance of grindability behaviour of a biomass fuel is crucial in power stations and pellet production for energy saving and maintenance costs especially in entrained-flow gasification and co-firing. Apart from that, great understanding of optimum torrefaction conditions is important to produce a torrefied biomass fuel that contains energy yield/density that is suitable for an efficient energy use. There has been increasing interests in designing a matrix approach that involves torrefaction parameters such as temperature, residence time and particle size. In this project, a continued research was developed, where the implication of Hardgrove Grindability Index was applied through correlations between the HGIequiv and carbon content, mass yields and energy yields.
There is also a limited research on the analysis of volatile products. There are studies that have successfully identified the gaseous and liquid products using GC-MS and TGA-FTIR, where samples were in powdered form, particles with less than 5 mm and some were in blocks. Many pyrolysis studies of biomass found the existence of mass and heat transfer limitations in bigger particle sizes upon higher temperature pyrolysis. Few studies have examined the influence of particle sizes on torrefaction. The primary focus of one of the researches was to determine the influence of particle sizes in terms of mass and energy yields. Some aimed to develop a kinetic model for torrefaction. In this project, the impact of different particle sizes on torrefaction with respect to the evolution of main volatiles as well as the properties of the torrefied biomass was investigated. This project develops method for the TGA-FTIR, where calibrations of FTIR for main gases were conducted.
Collection of liquid products involved condensation upon release from torrefaction reactor but not many literature reviews have described how it was done. In this project, laboratory methods for collection of liquids were developed, where few cold traps will be utilised. Characterisation of liquid products was investigated quite thoroughly, in which literatures are lacking. Liquids were separated into two phases: tar (organic) and water phase, where each phase was analysed differently.
Torrefaction modelling was implemented in this project through a software program, FG- Biomass to simulate the decomposition of biomass fuels during thermal treatment. It is able to predict the yields and rates of evolution of char, moisture, gases and other condensable organics with calculations. The output allows the comparison between the results obtained experimentally using the reactor and TGA-FTIR.
Finally, a short investigation on the combustion behaviour of torrefied biomass fuels was carried out for this thesis. To date, there are still gaps on how these torrefied biomass fuels respond to combustion. Similar experiments were carried out as those conducted by Bridgeman et al (2010), where they used a Meker burner flame. The approximate heating rate of the flame experienced by the biomass particles was determined with the use of FG- Biomass model. The rate of char combustion was predicted using the kinetic parameters determined by Jones et al (2012).