CHARACTERIZATION OF OLIVE RESIDUES FOR POWER
Transcripción
CHARACTERIZATION OF OLIVE RESIDUES FOR POWER
CHARACTERIZATION OF OLIVE RESIDUES FOR POWER GENERATION BY NEARINFRARED SPECTROSCOPY Jesús Mata Sáncheza, José Antonio Pérez Jiménez*a, Manuel Jesús Díaz Villanuevaa, Antonio Serranob, Nieves Núñezb, Jesús López Giménezc a Department of Biomass, CTAER Andalucía Foundation, Scientific and Technology Park, GEOLIT, Jaén (Spain) b NIR Soluciones, S.L., Rabanales 21 Science and Technology Park, Córdoba, Spain. c Department of Rural Engineering, Faculty of Agricultural and Forestry Engineering, University of Córdoba. *Corresponding e-mail: [email protected] ABSTRACT: The main objective of this work is to evaluate the viability of NIR technology as an efficient method for biomass characterization generated by olive residues. Solid biofuels quality parameters are determined by official methods established by the European Standard Technology Committee. Nevertheless, their implementation in the bioenergetic industry is scarce because these methods are expensive, tedious and time-consuming. Therefore, a faster, more reliable and cheaper analytical technique is mandatory in order to increase the quality control of these products in the bioenergetic industry. NIR spectroscopy is an eligible technique due to its high response speed, low cost per sample, absence of sample preparation, and versatility for the analysis of many different products and parameters. In this work, several biomass samples from olive industry such as olive stone, olive tree pruning (leaves, branches and a mixture of them) and dry solid olive waste (orujillo) have been analyzed in reflectance mode by using different NIR instruments without sample manipulation or only after a grinding up to 0.25 mm. The spectra showed a good absorbance in the representative NIRS regions; consequently, a great amount of information can be obtained. Keyword: Olive tree, quality standards, biomass, residues, NIR 1 INTRODUCTION Solid biofuels are a real option for thermic and electrical generation as alternative to the traditional generation from fossil fuels. Energy policy established by the European Union, Spain and Andalusia (Southern Spanish region) aimed at promoting renewable energy use and production. Due to its vast forest areas and mainly agricultural land use, Andalusia has a high potential for biomass generation. Within this context, olive industry is one of the main generators of solid biofuels both from residues generated in olive tree plantations and those generated by the olive oil industry. Only in Andalusia, the olive tree cultivated ground is over 1.400.000 Ha and the production of olive oil is over 800.000 t/year. In addition, residues generated by both agricultural activities represent a large bulk. For example, olive stones generated are over 450.000 t/year, olive pruning is over 2.000.000 t/year and orujillo residue is over 684.000 t/year (Economy, Innovation and Science Department of Andalucia Governement, 2011). From the point of view of energy stability and sustainable development, the energetic use of forest residues, agricultural and/or industrial by-products leads to a key strategic position for the future. The characterization of biomass is a substantial improvement in the valorization of these resources, allowing a rational and controlled use of its energy potential. Based on its quality parameters, solid biofuels could be managed to obtain a most efficient energetic valorization. Currently, solid biofuels quality parameters are determined by official methods established by the European Standard Technology Committee. However, their implementation in the bioenergetic industry is scarce because these methods are expensive, tedious and time-consuming. In this way, a faster, more reliable and cheaper analytical technique is required in order to increase the quality control of these products in the bioenergetic industry. NIR spectroscopy is, therefore, an eligible technique due to its high response speed, low cost per sample, absence of sample preparation, and versatility for the analysis of many different products and parameters. Near infrared radiation (NIR) covers the range of the electromagnetic spectrum between 780 nm and 2500 nm and it was discovered by Friedrich Wilhelm Herschel in 1800 (Davies, 2000). In NIR spectroscopy, the product is irradiated with NIR radiation, and the reflected or transmitted radiation is measured. While the radiation penetrates the product, its spectral characteristics change through wavelength dependent scattering and absorption processes. This change depends on the chemical composition of the product, as well as on its light scattering properties which are related to the microstructure. Understanding this phenomenon, it is possible to know the chemical constitution and physical parameters of the sample. Advanced multivariate statistical techniques are required to extract the required information from the usually convoluted spectra. Furthermore, NIRS technology is fully implemented in the agrifood industry for the determination of parameters such as moisture, protein, fiber, fat or sugar in a large number of products (Shenk et al., 2001; Muller and Steinhart, 2007) NIR radiation interacts with organic molecules and especially with structural groups O-H as in water, C-H, C-O, C-O-H and C=C bonds. These bonds are frequently found in biomass and they are related with important quality parameters like moisture, carbon content or energetic power. The main objective of this research is to evaluate the viability of NIR technology as an efficient method to analyze solid biofuels obtained from olive residues, in comparison with official methods. 2 MATERIALS AND METHODS. 2.1 Raw materials and sample preparation A sampling plan of olive residues such as olive stones, leaves, branches and orujillo were collected from different Andalusian industries. These samples have been b) 1 0.9 0.8 0.7 Absorbance (Log 1/R) analyzed by NIR technology and by official methods established by the European Standard Technology Committee. Near infrared spectroscopy analysis has been carried out without sample manipulation or after a grinding up to 0.25 mm. In this research, it has been analyzed 71 samples of olive stones, 20 samples of olive tree pruning and 16 samples of dry solid olive waste. 0.6 0.5 0.4 0.3 3. RESULTS AND DISCUSSION An example of duplicate NIR spectra corresponding to two representative samples of intact and ground olive stone, obtained by the instruments described above are shown in Figure 1. 0.2 0.1 0 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 Wavelength (nm) c) 1.6 1.2 Absorbance (Log 1/R) 2.2 Near-infrared spectroscopy In this study, spectral response for different types of intact and ground biomass has been obtained by different NIRS instruments. These instruments can be classified into three groups according to optic system and spectral region: a) NIRS instruments with monochromator and continuous spectrum, with a spectral region from 400 to 2500 nm collecting data every 2 nm. Sealed rectangular sample containers were used with a vertical transport module obtaining spectra all over the surface of the sample container. Each analysis takes 2 to 3 minutes. NIRS instruments such as FOSS or UNITY commercial firms are included in this group. b) Fourier transform near-infrared instrument with continuous spectrum and a spectral region from 12000 cm-1 (800 nm) to 4000 cm-1 (2500 nm) collecting data every 16 cm-1. Open round sample containers were used with a rotation system obtaining spectra all over the surface of the sample. Each analysis takes 20 seconds approximately. Commercial NIRS instruments from firms like BRUKER, BÜCHI or PERKINELMER are included in this group. c) Diode array NIRS instruments with a spectral region from 380 nm to 1690 nm collecting data every 3 nm. Open round sample containers were used. Each analysis takes less than one second. NIRS instruments like CORONA or PERTEN commercial firms are included in this group. 0.8 0.4 0.0 380 580 780 980 1180 1380 1580 Wavelength (nm) Figure 1. Sample spectra of intact (red) and ground (blue) olive stones obtained by duplicate analysis by instruments a), b), and c) As it is shown in Figure 1, differences between ground samples spectra are slighter than those obtained from intact sample spectra, being the duplicate spectra of the ground samples almost equal. Instruments type c) were discarded due to the absence of interesting bands in their spectral region (380-1690 nm), only the water band (1430 nm) could give information of interest. In the other hand, the most significant spectral region corresponds to the range between 1100 to 2500 nm, where characteristic absorption bands can be seen in the spectra obtained by instrument a) and b) at 1450 nm and 1930 nm corresponding to O-H bonds, at 1720 nm and 2300 nm corresponding to C-H bonds, or at 2100 nm corresponding to C-O bonds. 1.4 a) Olive tree pruning 1.2 1.0 Dry solid olive waste Olive stone 1.0 Absorbance (Log 1/R) Absorbance (log 1/R) Olive wood pellet 1.2 0.8 0.6 0.8 0.6 0.4 0.4 0.2 0.2 0.0 800 0.0 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 1000 1200 1400 1600 1800 2000 2200 2400 Wavelength (nm) Wavelength (nm) Figure 2. Intact sample spectra of different solid biomass from olive industry. 2600 In addition, spectra corresponding to olive stones, leaves, pruning, branches, olive tree firewood, and orujillo, are shown in Figure 2. As can be seen, spectra are very similar while significant differences are found in spectral region corresponding to the fat content (1720 nm and 2300 nm), being this effect more marked in olive stone and olive tree pruning. On the other hand, a spectral study of the solid biofuels samples has been carried out in order to detect similarities and differences among them and to establish different set of samples in the subsequent calibration model. Figure 3 shows the graphic representation of three first principal components of the solid biofuel spectra. A clear difference between solid biofuel spectra is found, being olive tree residues the solid biofuel most different. Despite of the possibility of developing a global chemometric model, it would be better to develop a specific calibration model for each kind of residue in order to obtain the best results and detect easily outliers. Figure 3. Graphic representation of spectral population of olive stone, olive tree pruning and orujillo. When a feasibility study of an NIRS application is performed, it is important to study the spectral repeatability in our samples. This study can be done with the statistical parameter called RMS (root mean squared). This parameter gives information about the spectral difference between a sub-sample and the spectral mean of some sub-samples of one sample. In this study it has been the spectral mean with 20 intact sub-samples for each type of sample. Solid biofuel RMS (A) RMS (B) Olive tree pruning 8000 10000 Olive stone 11500 14000 Dry solid olive waste 13500 12000 Table 2. RMS value of different products studied with instruments a) and b) These RMS values indicate that uniformity of samples is satisfactory for the use of NIRS technology. It is remarkable that olive tree pruning presents the lowest values of this parameter in spite of its heterogeneity. 4. CONCLUSION Based on the results NIRS technology could be used as a sustainable method to analyze solid biofuels from the official method data by using the spectral region between 1100 and 2500 nm. NIRS spectra information could be used to predict quality parameters such as moisture, carbon content , nitrogen content or net calorific value. NIRS method allows increasing the quality control of products in the bioenergetic industry and enables comprehensive traceability of raw materials and processes in order to a better use of resources. 5. REFERENCES Muller, A.; Steinhart, H. 2007. Recent developments in instrumental analysis for food quality. Food Chem. 102, 436-444. Shenk J.S., Workman J.J., Jr. and Westerhaus M.O. 2001. Application of NIR Spectroscopy to Agricultural Products. Handbook of Near Infrared Analysis. Second Edition. Burns D.A. and Ciurzack E. W. (eds). Practical Spectroscopy Series, Vol. 27. Marcel Dekker, USA. Davies, A.M.C., 2000. 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