On biomass milling for power generation

Biomass combustion has increasingly been used in pulverised fuel coal fired power stations as a way of addressing a wide range of emissions reduction targets. The reuse of existing equipment such as coal mills is essential to minimise the costs of conversion. However the fundamental fracture mechanics involved in biomass comminution are completely different to coal. Thus a thorough knowledge of the comminution properties of all biomass types in coal and biomass mills is necessary in order to minimise operational issues and to optimise milling and combustion. This thesis provides extensive novel characterisation on densified biomass before and after milling. The study analysed 9 densified biomasses, 2 non-densified biomasses, and a sample coal in five different mills; planetary ball mill, Hardgrove Grindability Index testing mill, Bond Work Index ball mill, cutting mill, and a ring-roller mill. Milling was found to have little impact on particle shape, even when an order of magnitude change in particle size was observed. Particle shape is inherent to the particles which comprise a pellet, and is determined by the pre-densified comminution processes. Milling had little impact on compositional particles of herbaceous or wood pellets. Olive cake had the most spherical of all the materials. Thermal pre-treatments of woody biomass not only saw a significant improvement in grindability in all mills, but also enhanced shape factors. The Hardgrove Grindability Index is a poor indicator of the grindability of biomass. The Bond Work Index can be used to analyse the choking potential of biomass pellets prior to full scale mill trials. To optimise milling in coal mills, biomass pellets should be composed of particles close to the required size so that only the pellet comminution stage occurs. The milling behaviour of densified biomass in a laboratory scale ring-roller mill with dynamic classification was investigated for the first time. The milling studies showed that knowledge of a materials critical particle size for comminution through compression is essential to understand its milling behaviour in different mills. The results presented in this thesis not only provide new insight and addresses significant gaps in knowledge, they also provide useful and practical guidance for addressing operational issues such as mill choking, as well as ways to optimise biomass comminution in laboratory and full scale mills, such as mill classifier optimisation based on real particle characteristics

Applicability of mechanical tests for biomass pellet characterisation for bioenergy applications

In this paper, the applicability of mechanical tests for biomass pellet characterisation was investigated. Pellet durability, quasi-static (low strain rate), and dynamic (high strain rate) mechanical tests were applied to mixed wood, eucalyptus, sunflower, miscanthus, and steam exploded and microwaved pellets, and compared to their Hardgrove Grindability Index (HGI), and milling energies for knife and ring-roller mills. The dynamic mechanical response of biomass pellets was obtained using a novel application of the Split Hopkinson pressure bar. Similar mechanical properties were obtained for all pellets, apart from steam-exploded pellets, which were significantly higher. The quasi-static rigidity (Young’s modulus) was highest in the axial orientation and lowest in flexure. The dynamic mechanical strength and rigidity were highest in the diametral orientation. Pellet strength was found to be greater at high strain rates. The diametral Young’s Modulus was virtually identical at low and high strain rates for eucalyptus, mixed wood, sunflower, and microwave pellets, while the axial Young’s Modulus was lower at high strain rates. Correlations were derived between the milling energy in knife and ring roller mills for pellet durability, and quasi-static and dynamic pellet strength. Pellet durability and diametral quasi-static strain was correlated with HGI. In summary, pellet durability and mechanical tests at low and high strain rates can provide an indication of how a pellet will break down in a mill

Eco-score labels on meat products: consumer perceptions and attitudes towards sustainable choices

Non-profit organisations have developed labelling strategies to communicate the environmental impact of food products, helping consumers make more informed purchase decisions. The evidence on whether environmental food labelling can change behaviours toward environmental meat choices is unclear, due to context factors within shopping environments and differences in attitudes towards meat and the environment. This study investigates attitudes towards an eco-score label on meat products by measuring the influence of meat and environmental attitudes and identifying drivers and barriers through a mixed-methods design. An online questionnaire (N = 255) posed questions concerning meat consumption, label perceptions, and use intentions. Recruitment was via convenience sampling under the criteria of UK dweller, omnivorous diet and over 18 years of age. Nine semi-structured interviews explored the drivers and barriers for intended use through thematic analysis. Perceptions Scores (PS) and Purchase Intention (PI) scores of the label were positive. Results showed an individual's Meat attachment (affinity) score (MAAS) negligibly influenced PS but provided a moderately negative relationship with PI. Environmental label use and attitudes positively influenced PS and PI. The qualitative data identified label design and concept perceptions as drivers for use, whereas habitual shopping behaviours and perceived price were barriers. The research contributes to the transtheoretical model of behavioural change, identifying that 58% of participants contemplate label use but require more information. Explanations found for the gap between positive perceptions and low behavioural intentions support this, as poor label awareness and knowledge of the environmental impact of meat production were highlighted

Influence of mill type on densified biomass comminution

The impact of different mill fracture mechanisms were examined for a wide range of densified biomass pellets to provide a comprehensive analysis of biomass milling behaviour for pulverised fuel combustion. The milling behaviour of 7 woody, herbaceous, fruit, and thermally treated densified biomasses were investigated for four distinct types of comminution fracture mechanism using traditional milling indices and novel application of 3D imaging techniques. For the coal mill trials, a reference coal was used to provide a milling performance comparator. For the pre-milled samples, woody and herbaceous pellets have the least spherical particles (φ 0.324–0.404), followed by thermally treated pellets (φ 0.428), La Loma coal (φ 0.503), with olive cake having the most spherical particles (φ 0.562). This trend was noted for all the shape factors. Conventional comminution did not significantly impact biomass particle shape, even after a significant change in particle size. Therefore biomass pellet process history plays a key role in determining the comminuted particle shape. La Loma coal had significantly enhanced milling performance in comparison to the biomasses in the coal mills. Significant improvements in grindability and shape factors were observed for the thermally treated pellets. Mill choking was experienced for several of the woody and herbaceous samples, which resulted in a significant energy penalty. The mechanisms of mill choking were found to be intrinsically linked to the critical particle size of comminution through compression, particle shape factors, and the Stokes conditions set for the classifier and burners in pulverised fuel combustion systems. The study showed that for optimal milling performance, biomass pellets should be composed of particles which meet the Stokes requirements of the mill classifier. This would minimise the potential for mill choking and milling energy penalties, and ensure maximum mill throughput

Predictability of higher heating value of biomass feedstocks via proximate and ultimate analyses – A comprehensive study of artificial neural network applications

Higher heating value (HHV) is a key characteristic for the assessment and selection of biomass feedstocks as a fuel source. The HHV is usually measured using an adiabatic oxygen bomb calorimeter; however, this method can be time consuming and expensive. In response, researchers have attempted to use artificial neural network (ANN) systems to predict HHV using proximate and ultimate analysis data, but these efforts were hampered by varying case specific approaches and methodologies. Based on the complex ANN structures, a clear state of the art ANN understanding must be required for the prediction of biomass HHV. This study provides a comprehensive ANN application for HHV prediction in terms of how the activation functions, algorithms, hidden layers, dataset, and randomisation of the dataset affects the prediction of HHV of biomass feedstocks. In this paper we present a comparative qualitative and quantitative analysis of thirteen different algorithms, four different activation functions (logsig, tansig, poslin, purelin) with a wide range of hidden layer (3–15) for ANN models, used to predict the HHV of the biomass feedstocks. ANN models trained by the combination of ultimate-proximate analyses (UAPA) datasets provided more accurate predictions than the models trained by ultimate analysis or proximate analysis datasets. Regardless of the used datasets, sigmoidal activation functions (tansig and logsig) provide better prediction results than linear activation function (poslin and purelin). Furthermore, as training activation functions, “Levenberg-Marquardt (lm)” and “Bayesian Regularization (br)” algorithms provide the best HHV prediction. The best average correlation coefficients of 30 randomised run were observed with tansig as 0.962 and 0.876 for the ANN model developed by the UAPA dataset with a relatively high confidence levels of ∼96% for training and ∼92% for testing

Experimental data on morphological characterization of chars from coal and bagasse blends

© 2020 The Authors Morphological characterization of chars from coal and bagasse plays an important role in both the burning efficiency and intrinsic reactivity of chars, during a combustion process [1], [2]. In this work, abundant data on the morphology of chars produced from coal and bagasse blends are presented. Char synthesis was performed varying the temperature (900, 1000 and 1100 °C) and bagasse proportion feeding (0, 25, 50, 75 and 100% w/w) in the pyrolysis reaction. Proximate, ultimate, petrographic and vitrinite reflectance of raw coal and bagasse are presented. Char morphology is classified into three groups -- thin walls, thick walls, and solid particles--, and results are exhibited. The data set is a comprehensive source for advancing in a further understanding of char's morphology from coal-bagasse blends

High capacity chipless RFID tags for biomass tracking application

The design of a low-cost, flexible, miniaturized and a high code density chipless RFID tag is presented as a solution for tracking the transportation of biomass fuel pellets. The performance of the tag is presented and demonstrates the applicability of the design for different material systems, whilst maintaining a compact size of 5.06cm 2. The tag consists of nested concentric hexagonal elements and a central spiral resonator suitable for ID encoding. The tag presented demonstrates code density of 3.6-bits/cm 2 , possesses angular stability up to 60º and high radar cross-section. The tag performance was also observed for tracking 5kg of fly ash biomass. Additionally, as the tag mass mostly consist of FR4, PET or Taconic TLX-0 with a minute mass of either copper, gold or silver, the tag can be easily combusted and disposed of during biomass combustion. The novel features of this tag are the combination of hexagonal and spiral shape slots for maximum space utilization thereby achieving high RCS signatures along with high code density. All these properties of the proposed chipless RFID tag provides a pioneering pathway for a real-time biomass tracking application. Keywords: Authors should not add keywords, as these will be chosen during the submission process (see http://journals.cambridge.org/data/relatedlink/MRF_topics.pdf for the full list

Microwave pyrolysis of Laminaria digitata to produce unique seaweed-derived bio-oils

Microwave pyrolysis has become an attractive form of processing technology to generate bio-oil, bio-char and syngas from different biomass feedstocks. In this study, microwave pyrolysis was performed on the UK native seaweed Laminaria digitata and its extract residue from a bio-refinery process. Pyrolysis of these two feedstocks was successfully achieved without the requirement of microwave susceptors, as pelletizing the biomass was sufficient to allow microwave pyrolysis to occur. It was found that average energy requirements as low as 1.84–2.83 kJ g−1 were required to pyrolyse 55–70% of both feedstocks and bio-oil yields of 5–8% and 10–14% for native and extraction residue L. digitata were produced, respectively. Maximum microwave pyrolysis processing times were in the order of 200 s. The bio-oil generated from both feedstocks contained no phenolic based compounds, but a greater number of nitrogen-containing compounds and compounds derived from macroalgal polysaccharides. Yields of certain compounds differed in bio-oils generated from the two L. digitata feedstocks, however it was observed that specific energy did not have a direct influence on bio-oil compound yield. Furthermore, the identification of a particular nitrogen-containing compound L-Proline, 1-methyl-5-oxo-, methylester is thought to be a unique product of microwave pyrolysis when carbon-based additives are avoided

Formation of Metallurgical Coke within Minutes through Coal Densification and Microwave Energy

This paper shows how feedstock densification gives rise to a step change in the time required to create a metallurgical grade coke using microwave energy. Five densified coking and non-coking coals were heated in a multi-mode microwave 2450 MHz cavity for varying treatment times (2-20 minutes) with a fixed power input (6 kW). Proximate analysis, intrinsic reactivity, coke reactivity, dielectric properties, and petrographic analysis of the coals and microwave produced lump cokes were compared to a commercial lump coke. Densifying the sample prior to microwave treatment enabled a dramatic acceleration of the coking process when combined with targeted high microwave energy densities. It was possible to form fused coke lump structures with only 2 minutes of microwave heating compared to 16-24 hours via conventional coking. Anisotropic coke morphologies (lenticular and circular) were formed from non-coking coal that are not possible with conventional coking and increasing treatment time improved overall coke reflectance. Three of the coals produced coke with equivalent coke reactivity index values of 20-30, which are in the acceptable range for blast furnaces. The study demonstrated that via this process, non-coking coals could potentially be used to produce high quality cokes, potentially expanding the raw material options for metallurgical coke production

The impact of moisture on the milling behavior of different biomasses

The aim of this study was to examine the impact of moisture content on the milling behaviour of four different biomasses commonly used in the power sector and characterise their milling behaviour in a laboratory scale planetary ball mill. As received (raw) and dried wood pellets, eucalyptus pellets, olive pellets, and Spanish olive cake were milled for the same milling conditions, and then characterised by energy consumption, particle size, and thermal characterisation. The study found that dry samples have higher energy consumption than raw samples in a laboratory scale planetary ball mill. Drying had varying impacts on the particle size distributions of the samples, with olive cake showing a 60% reduction in mean geometric diameter, while wood and eucalyptus pellets only showed a 15% and 18% reduction respectively. Moisture acts an inhibitor to milling performance, and increased moisture makes biomass more impact resistant, thus reducing ball momentum and resulting in lower energy consumption in the mill