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EXOTHERMIC EVENTS OF NUT SHELL AND FRUIT STONE PYROLYSIS Colomba Di Blasi, Antonio Galgano, and Carmen Branca ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.9b01474 • Publication Date (Web): 18 Apr 2019 Downloaded from http://pubs.acs.org on April 20, 2019

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ACS Sustainable Chemistry & Engineering

EXOTHERMIC EVENTS OF NUT SHELL AND FRUIT STONE PYROLYSIS C. Di Blasi+*, A. Galgano++ , C. Branca++ Dipartimento di Ingegneria Chimica, dei Materiali e della Produzione Industriale, Università degli Studi di Napoli "Federico II", P.le V. Tecchio, 80125 Napoli, Italy. ++ Istituto di Ricerche sulla Combustione, C.N.R., P.le V. Tecchio, 80125 Napoli, Italy * corresponding author Tel:39-081-7682232; e-mail:[email protected] +

Abstract Pyrolysis is carried out by means of a packed bed, heated along the lateral surface at a moderate temperature (about 585K), of a significant number of nut shells (pine, macadamia and Brazil nuts, hazelnut, walnut, almond, coconut, chestnut, peanut, pistachio) and fruit stones (olive, nectarine, peach, plum, cherry, apricot). With the exception of pistachio shells, the residues own fixed carbon (and C) and lignin/extractive contents higher than those of wood. The SEM images of chars reveal a non-porous vesicular or foamed tissue generally crossed by a very few large hollow vessels surrounded by bundles of small void fibers and/or hosting elongated rolled elements again of much smaller size. The EDX analysis indicates that the deposits, scattered on the charred tissue, are generally rich in potassium. As a consequence, secondary reaction activity is enhanced and, compared with wood, pyrolysis-induced overheating is always higher. However, despite the similarities, feedstock differences during pyrolysis are remarkable, as testified by maximum temperature overshoots between 60- 225K (versus 50K for wood) and severe pyrolytic runaway established only for about the half of the samples. Key Words: biomass; packed bed; agro-industrial residues; pyrolysis reaction heat; overheating; char microstructure, SEM images, INTRODUCTION Pyrolysis is an important technology for the production of renewable bio-fuels and chemicals from biomass. Massive investigations have been carried out in an attempt to clarify the chief fundamentals of the reaction mechanisms (see, for instance, the recent notes1,2), nevertheless the current knowledge is still limited owing to the highly variable chemical properties and the scarce development of advanced experimental techniques.3 Moreover, the understanding of the key variables and mechanisms controlling the product yields and composition for practical systems is further complicated by the interaction between chemical and physical processes,4 the scarce knowledge of transport properties,5,6 which also limits the development of detailed predictive models, 7-10 and the somewhat unexpected magnitude of the conversion exothermicity.11 As clearly demonstrated for thick particles or packed beds uniformly heated along the lateral surfaces, 12-20 biomass pyrolysis can be a highly exothermic process. Moreover, previous studies of this research group have for the first time shown that some agro-industrial residues21-25 and acid or alkaline pre-impregnated wood,26-29 when exposed to mild external heating conditions that for raw wood barely results in torrefaction, undergo a new and hardly controllable conversion regime ACS Paragon Plus Environment

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named pyrolytic runaway. This is identified with a very rapid overheating of the entire sample, up to temperatures about 300K higher than the external heating temperature for a bench-scale pyrolyzer,25 with the consequent almost instantaneous release of the entire volatile matter content. The highly variable biomass properties, which hinder the development of comprehensive models of general validity, are also expected to affect the reaction heats and thus the global thermicity of the conversion. From the practical point view, given the determinant role played by the temperature for the pyrolysis characteristics and the need to optimize yields and quality of products, it can be useful to understand whether a similarity of the feedstock physical appearance also means a comparable thermal behavior. In this way, in addition to an improved understanding of the factors causing remarkable exothermicity often associated with pyrolytic runaway, a possible grouping originating from similar chemico-physical properties or botanical family could be searched. More specifically, as the packed-bed pyrolysis of hazelnut shells21-24 is known to be particularly critical in relation to exothermicity, it would be desirable to understand whether other nut shells and fruit stones also behave similarly. However, no investigation has yet been carried out about these aspects. In this study a significant number (N. 16) of agro-industrial residues, that are commonly classified as nut shells and fruit stones, are investigated in relation to their pyrolytic conversion in a packed bed. The thermal dynamics and the yields of the lumped classes of products are examined. Moreover the samples are characterized, by means of thermogravimetry, in relation to proximate analysis and decomposition temperatures and, by means of Scanning Electron Microscope (SEM) and Energy Dispersive X-ray (EDX) methods, in relation to the microstructure of the pyrolysis chars. MATERIALS AND METHODS The materials investigated can be grouped based on their appearance as nut shells (hazelnut, walnut, almond, coconut, pine, macadamia and Brazil nut, chestnut, peanut, pistachio) and fruit stones (olive, nectarine, peach, plum, cherry, apricot). However, as for the first group, 30 the true nuts are only hazelnut and chestnut while almond, walnut, coconut and pistachio are classified as drupes. Brazil and macadamia nuts are a capsule and a follicle, respectively. Finally peanut and pine nuts are actually a legume and a gymnnosperm. Peaches, nectarines, plums, apricots and cherries are all members of the Prunus genus while olives belong to the Olea genus. All of them are drupes. The samples are mainly residues from plants grown in South Italy (hazelnut, walnut, ACS Paragon Plus Environment

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almond, pine, chestnut, peanut and pistachio shells; olive, nectarine, peach, plum, cherry and apricot stones). In a few cases they are the processing wastes of imported goods (Brazil and Macadamia nuts, from Brazil and Australia, respectively). The common factor to all the samples is that they are the lignocellulosic involucres of seeds which, for the majority of them, appear as more or less compact woody structures. Beech wood is used for comparison. Pyrolysis experiments are carried out by means of a packed-bed bench-scale system whose details are already reported in previous work of this group15-17,21-29 and summarized in the attached Supplementary Material. A cylindrical bed (40mm diameter and height) is exposed along the lateral surface to a heat flux irradiance of 23kW/m2, corresponding to an average heating temperature, TS, of 585K. This temperature is that reached by the char bed, at the conclusion of the conversion process, at a distance of 5mm from the heat exposed surface. The variation is around ±8K, attributable not only to the different thermal properties of the chars but also to their yields and shrinkage which affect the bed height and the heating conditions. This external heating condition gives rise to maximum temperature overshoots and pyrolytic runaway for hazelnut shells.21-24 During the experiments, the bed temperature is monitored at the median section by five thermocouples, starting from r=0 (center) to 19mm (subsurface). Also the yields of the lumped product classes (char, gases and liquids) and the gas composition are measured. The samples subjected to packed-bed pyrolysis consist of particles prepared so as to retain the original thickness of the residues (0.5-4mm) and widths around 2-6mm, as summarized in Table 1. Although the bulk density of the bed affects the pyrolysis characteristics,31 in order to preserve the material microstructure, pulverization to prepare pellets of equal density has been avoided. Hence the sample mass depends on the specific material. Only for peanut and chestnut shells, briquettes of about 5mm size have been prepared using particles again preserving the original thickness and widths around 0.8-1mm. Nevertheless, the range of variation of the initial sample mass is not exceedingly high (values of 25-31g, with the large majority around 28-29g). The reference sample, beech wood, is considered in the form of pellets (consisting of particles sized around 1-2mm) so that the initial sample mass (28g) is comparable with that of the other samples. For the mild thermal conditions applied during heating and the size of the bed it has already been shown16 that, for this feedstock, the particle size does not play a crucial role. Table 1 also lists the decomposition temperature, Tdec, as determined from thermogravimetric curves (measured by means of a Mettler TGA/1 system) for a sample mass of 5mg and particle sizes below 80m, heated at 5K/min up to 773K under a nitrogen flow of 50ml/min. More ACS Paragon Plus Environment

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precisely it is the temperature corresponding to the release of 50wt% of the total volatile content. It is well known that lignocellulosic biomass decomposes over a more or less wide temperature interval, however, to facilitate the comparison among the various samples, this approximate definition is anyway useful. The Tdec range of variation is 574-600K (versus 592K of beech wood) but the large majority of the samples exhibits values around 585K, that is, the average heating temperature, TS. In fact, this condition permits an optimal display of the global exothermicity of the pyrolysis reactions for the heating modality of the packed-bed pyrolyzer of this study.25 Sample characterization is made in terms of proximate analysis using a thermogravimetric system (Mettler TGA/1) with the application of the method already described in Ref. 32. The information about the chemical composition and ultimate analysis is derived from previous literature. Also, the microstructure of the chars is investigated by means of SEM and EDX analyses (only the chestnut shell char is not subjected to this last characterization). RESULTS AND DISCUSSION The chief characteristics of nut shells and fruit stones, including proximate and ultimate analysis, chemical composition and char microstructure, are first discussed. Then the thermal field and the yields of products measured for the packed-bed pyrolysis (external heat flux intensity of 23kW/m2, corresponding to TS of 585K) are examined. Sample Characterization The chemical composition of biomass is known to play a key role in relation to yields and composition of products. Consequently it is expected that the display of peculiar thermal events associated with reaction heats will also be affected. The classes of residues examined mainly consist of the standard chemical components (extractives, cellulose, hemicellulose and lignin) whose contents on a dry and ash-free basis, obtained from a careful analysis of previous literature, are detailed in Table S1A of the Supporting Information. The average values are summarized in Fig. 1A, where beech wood is used for comparison. Separate contents of hemicellulose and cellulose are reported, except for the Brazil nut shells. Moreover, the role of the specific variety of peach (yellow or nectarine) on the stone composition is not known. Despite the significant number of investigations examined, the deviations, even for the same feedstock, are high. Apart from the influence of the plant variety and the geographical origin, it is likely that the method and accuracy of the analysis as well as the sample properties (i.e. particle size) are also important. Excluding pistachio shells, all the residues are characterized by a rather high lignin content (average value of ACS Paragon Plus Environment

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39wt%), well above that reported for standard hardwoods and softwoods (around 22 and 29wt%, respectively).33,34 The content of extractives and other components (e.g. proteins for peanut shells, with an average value around 6 wt%) is also generally higher that that observed for the wood varieties, though the scatter, even for the same residue, is again high. Conversely, the content of cellulose (average value around 30wt %) is much lower than that typically found for wood (around 43wt%,33,34). Lower contents of hemicellulose are also observed with an average value around 21 wt % (versus of 35 and 28% hardwoods and softwoods, respectively). 33,34 As anticipated, pistachio shells are an exception to this trend. This residue owns cellulose contents higher (about 58wt%) than those of standard woods, with hemicellulose and lignin contents around 20wt%. The results of the sample proximate analysis are listed in Table S1B (Supporting Information) and plotted in Fig. 1B. These are in line with those of the chemical composition. Indeed, excluding pistachio shells, the fixed-carbon contents of the residues (14.5-25.5wt%) are generally higher than those of wood (13 wt%), most likely owing to the higher fixed-carbon content of lignin and extractives,35 compared with those of cellulose and hemicellulose. In particular, the highest FC contents (around 25wt%) are observed for the Brazil nut and chestnut shells. Moreover, again in line with the high cellulose content, the proximate analysis of pistachio shells reports the lowest fixed-carbon content (about 11wt%). As already noticed for the data on the chemical composition, the literature values for the ultimate analysis of the samples also are significantly different among the various authors. However, it is interesting to notice that, with reference to a data set produced by the same laboratory36 for the large part of the samples of interest in this study (Table S1C of the Supporting Information and Fig. 1C), again with the exclusion of pistachio shells, the C contents of the residues (50-54.4wt%) are generally higher than those of wood (50wt%). This is most likely again a consequence of the higher C content of lignin (60wt%), compared with those of cellulose and hemicellulose (around 43 and 46 wt%, respectively).36 Morphological Structure of Chars The product distribution, and consequently the exothermicity display, from biomass pyrolysis are the result of primary and secondary reaction activity.4 As secondary reactions mainly occur at the microstructure level,37-39 it is useful to examine SEM and EDX analyses of the samples. Given that the particle sizes used for packed-bed pyrolysis are sufficiently thick to preserve the original material structure and that the conversion process, causing the partial release of the volatile content, puts into more evidence the structural details, the analysis is made for the char samples. ACS Paragon Plus Environment

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In contrast with the wood microstructure,8 the chars originated from both shells and stones are always characterized by a cellular or vesicular network similar to a sponge, with closed or open alveola closely interconnected (though not examined in this study, the chestnut char structure also presents the same chief features40). These features are clearly visible from Figs. 2A-2D, Figs. 3A3D, Figs. 4A-4D, Figs. 5A-5D and Figs. 6A-6D. In the vast majority of cases, the foam-like structure is crossed by void fibers of large diameter (indicated by a green arrow) similar to the vessels typical of hardwoods, as can be observed from the frontal views of the particle thicknesses (Figs. 2A-2D, Figs. 3A, 3B, 3D). However, contrary to wood, their number is very small and therefore it is expected that they scarcely contribute to the actual medium micro-porosity. In some cases (hazelnut, macadamia and Brazil nut shells) the vessels host bundles of small helicoidally shaped fibers (Figs.2A (indicated by a pink arrow), 5C, 5D). In other cases (almond and coconut shells, olive, nectarine, apricot and prune stones), in the neighborhood of the vessels, bundles of small void fibers are visible (Figs. 2D, 3B, 4B, 4D, 5A, 5B, 6B, indicated by a yellow arrow), similar to softwood tracheids. Also, fibers of various diameters (indicated by a yellow arrow) are often located only immediately underneath the external surface of the shell/stone, as shown by the examples of cherry stones and peanut shells of Figs. 3B, 3C, 5B. Void fibers seem to lack only for pistachio and pine nut (Figs. 6C, 6D) and chestnut shells. In the first case flaky structures are visible. Magnifications of the sponge-like structure can be seen from Figs. 4A, 4C. SEM images of the shell and stone chars also show deposits over the internal and external surfaces and the cross section of the particles, as shown by Figs. 7A-7D for the olive and cherry stones and the pistachio and Brazil nut shells (the magnified view permits to clearly observe the numerous deposits for the olive stones whereas, in the other cases, they are indicated by arrows). EDX analysis, carried out for N. 3-6 items, reveals that the main constituents are always carbon and oxygen with the presence of inorganic compounds including K, Na, Mg, Al, Ca, Si and Fe and, for olive stone, Cl. Given its catalytic role in pyrolysis, it should be noticed that K is present in significant amounts, with values around 0.5-2wt% (apricot, peach, nectarine and cherry stones), around 2-6wt% (hazelnut, walnut, pine nut, Brazil nut, coconut, peanut, macadamia and pistachio shells and plum stones) and around 3-13wt% (almond shells and olive stones; for the latter Cl is also detected with values of 1-8wt%). The amount of Mg is around 0.5-1wt%, with the exception of almond shells with values up to 2-4wt%. The presence of Na is observed only in a few cases (walnut, coconut and pistachio shells, and peach, olive and plum stones) with values around 0.5-

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3wt%. The amount of Ca, detected in all cases, is comprised between 0.5-6 wt%. Ca, K and Mg are also the main constituents of chestnut shell ashes.41 These findings are, for main lines, in agreement with the current state of knowledge about the ash composition of the residues. As shown by the analyses discussed above, compared with wood, the ash contents of the residues vary over a wider interval and, what is more important, the contents of alkali compounds may be much higher. According to Ref. [42], the K2O content, the most abundant alkali component of the high temperature ashes, is very high for almond shells, olive residues and plum stones (around 45-50wt%), followed by hazelnut and walnut shells (around 30wt%), pistachio shells (19wt%) and peanut and coconut shells (around 8.5wt%) (versus typical values of 6-8wt% for wood). It should be stressed that the presence of indigenous or added alkali compounds profoundly modifies the pyrolysis reaction paths and products and, what is more important for this study, the thermicity of the conversion,20,28,29 with the possible transition, also for wood, from a mild exothermic process to pyrolytic runaway. Packed-bed Pyrolysis The dynamics of the thermal field for the various samples confirm that pyrolytic conversion is always exothermic, as clearly evident from the temporal profiles of the spatially averaged temperatures, Ta, at the median bed section, reported in Fig.8 (to put into evidence the reactioninduced overheating, the average heating temperature, TS, is also indicated by a dashed line). The magnitude of these effects is sample dependent and always higher with respect to beech wood. For a first basis comparison, the average radial temperature of the bed, Tmaxa, at the time tmax corresponding to the attainment of the maximum temperature, Tmax, (and related maximum overshoot, T, referred to the steady conditions of the char bed) can be used (the temperature Tmaxa is already used, in the Figs. 1A-1C and Table 1 previously introduced, for sample numbering starting from the maximum to the minimum display of exothermicity). It incorporates the effects of both the temperature overshoot and the size of the overheated zone for the most critical conditions. In fact not only the global amount of heat released from the conversion process is important but also the global rate of heat release as very fast exothermic processes are extremely difficult to control.25 It should be anticipated that the sample numbering (or the "conversion property" Tmaxa that can be considered the summa of the combined action of the chemical and physical properties of the various samples) will also be used in the following as a correlation parameter for the characteristic times and temperatures and the product yields. The radial temperature profiles at tmax are grouped in Fig.9 with the inclusion of the steady averaged profile ACS Paragon Plus Environment

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reached by the inert char bed (the actual range of variation of the steady temperatures is again around ±8K), Tchar, and the list of the tmax values. The data of Fig.9 support the introduction of three feedstock groups: I) the first group consisting of eight samples (cherry, peach, nectarine, apricot and olive stones, hazelnut, almond and walnut shells) with the highest Tmax and the radius of the uniform central core of about 15mm (Tmaxa between 765-717K and T between 225-194K), II) the second group consisting of five samples (pine nut, coconut, Brazil nut and peanut shells and plum stones) with intermediate Tmax values and the radius of the central uniform core around 10mm (Tmaxa between 703-681K and T between 136-176K), and finally III) the third group including three samples (macadamia nut, chestnut and pistachio shells) characterized by limited overheating for a bed core with a radius of about 5mm (Tmaxa approximately between 652-627K and T between 104-62K). The Tmaxa and T values for beech wood are 627 and 53K, respectively. From the quantitative point of view, even the third group exhibits a pyrolytic behavior more exothermic than that of beech wood, confirming that the thermicity of agro-industrial residue pyrolysis requires a more careful consideration. As expected, the highest radial gradients are established in the neighborhood of the bed surface owing to external heat losses (the bed temperatures during conversion are higher than the external heating temperature). Examples of the heating dynamics for the three feedstock groups introduced above are reported in Figs. 10A-10D (each panel also includes the steady temperature profile of the char bed for each specific sample). For exothermic conversion and decomposition temperatures comparable with the heating temperature, the thermal dynamics always roughly consist of three main more or less sequential stages: induction (or preheating), reaction-induced overheating, thermal decay. The induction (or preheating) time, ti, can be associated with a sudden rapid increase in the bed heating rate at any position, indicated as trigger point (or zone) or, in alternative, with the attainment of temperature values higher than the decomposition temperature across a subsurface layer (as testified by the thermocouple positioned at r=15mm).25 It is logical that the decomposition reactions are already active at times shorter than the induction time but their rates are still too slow to self-accelerate the process. Moreover, it is understandable that an assigned constant heating rate or temperature cannot be selected a priori to define the position of the trigger point. In fact the characteristics of this point/zone depend on the sample properties and the external heating conditions.25 The temperature profiles at the induction time (together with the list of the ti values) are plotted in Fig.11, where the position of the trigger point is indicated by a void circle. ACS Paragon Plus Environment

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When the heating temperature is barely lower than the feedstock decomposition temperature and the exothermicity of the process is remarkable, the trigger point is observed at an internal position, generally the center, of the bed. Instead, for the opposite case (heating temperatures barely higher than the decomposition temperature and/or limited exothermicity making comparatively more important the heat losses), the trigger point is generally located nearby the sample surface. For the first two feedstock groups, as a consequence of the strong exothermicity, the role of the external heat source is essentially that of a process initiator and the thermal dynamics are closely related to the occurrence of the pyrolysis reactions. Instead, for the third feedstock group, given the limited exothermicity, the externally provided heat also contributes, in significant

amount, to bed

preheating. Moreover, owing to the slow rate of heat production, the local heating rate of the trigger zone may also be rather slow owing to the dispersion of the reaction generated heat towards both the external surface and the inner colder zones of the bed. In general, for trigger points located in the neighborhood of the external surface, the radial temperature gradients, at the induction time, are higher and overheating (and conversion) approximately take place first across the more external bed annulus and then for the central core. In any case, it should be stressed that, for moderate external heating conditions barely sufficient to initiate the decomposition process, the global magnitude of the exothermicity always plays a key role for the thermal conditions that are actually established during conversion. The temperature profiles at the induction time plotted in Fig.11 confirm the establishment of relatively small radial gradients and show the position of the trigger points. As expected on the basis of the decomposition temperatures (591-600K), hazelnut and pine nut shells and cherry stones exhibit an internal (bed center) trigger point. Also, decomposition temperatures below 575K make understandable a subsurface trigger point for almond and coconut shells and olive stones. For these samples as well as for those of the third group the radial gradients of temperature at the induction time are the highest. On the other hand, for the samples with Tdec values between 581588K, the trigger point is observed either at the center or the surface of the bed most likely as a consequence of the approximate definition of the decomposition and heating temperatures. It should be noticed that an induction time in biomass pyrolysis can be defined independently from the

magnitude of the reaction-induced overheating and the differences between

decomposition and heating temperatures. In fact, for significant differences between these two, the consequent increase in the spatial gradients gives rise to the well known conversion dynamics dominated by the simultaneous existence of several zones along the bed radius (i.e. charred, ACS Paragon Plus Environment

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reacting and unreacted zones).7,8,43 Therefore the stages of preheating, reaction induced overheating and decay are no longer sequential. Also, the heat released at the reacting zone is largely exploited for feedstock preheating so that the exothermicity display becomes much less evident.25 For the mild heating conditions of the shell and stone pyrolysis of this study, the other two process stages are qualitatively similar. The most evident feature of the overheating stage is the rise of the temperature, above the external heating one, as a consequence of exothermic pyrolysis until the absolute maximum is attained. It is expected that the large part of the conversion takes place during the overheating stage, especially in the presence of strong exothermicity. Indeed, in this case, the third stage of the process, consisting of the temperature decay towards the external heating value, is generally rather rapid. However, it is understandable that, given the still high temperatures, devolatilization may also occur at a certain extent during this last stage, especially for the samples with lower exothermicity and/or higher Tdec values. As expected (and shown by the values reported in Figs.9,11), the shortest ti and tmax values are observed for the most reactive (low Tdec values) samples, i.e. almond and coconut shells and olive stones. Moreover apart from the relatively short values for pistachio shells, attributable to the peculiar chemical composition consisting of large cellulose amounts, these characteristic times tend to increase as the global exothermicity of the process decreases (some scatter can be due to the differences in the reactivity and initial sample mass). The temporal profiles of the rate of gas release (defined as the time derivative of the percentage of gas released), reported in Fig.12, show that the reaction exothermicity also affects the global rate of mass loss. In fact, despite the different chemical properties, the maximum rate of gas (and most likely vapor) release increases whereas the duration of the devolatilization process decreases as the observed Tmaxa becomes successively higher. The rate of volatile release is also important because, together with the material microstructure, it contributes to determine the intra-particle residence time and concentration of the vapors and thus the extent of secondary reactions. Though not shown, it is useful to point out that the percentage of gas released at the induction time is approximately comprised between 18-22% of the total amount (25% for the macadamia and chestnut shells of the third group), indicating that the decomposition process is underway. This is also an "a posteriori" confirmation of the validity of the selected ti values. To quantitatively compare the global exothermicity of the various samples during packed-bed pyrolysis, it is also useful to introduce, with the aid of the curves plotted in Fig. 13 as an example, ACS Paragon Plus Environment

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the average spatial temperature at the induction time, Tia, and the average temperatures referred to the actual overheating and conversion intervals, Toverh and Tconv. The actual overheating interval is defined as the difference between tmax and ti, toverh = tmax-ti (see Fig. 13). In previous studies of this group,21,25 the conversion time has been assumed to correspond to conditions of maximum display of the reaction exothermicity (i.e. the attainment of the maximum temperature), tmax, given the significant magnitude of these effects. However, a more general evaluation of the conversion time can be made using the decay time, td, that is, the time required for the maximum temperature to decrease by 90% (see Fig. 13). Hence, the time interval where conversion actually takes place, after the induction period, can be defined as the difference between the decay and the induction times, tconv=td-ti (see Fig. 13). Similar to the ti and tmax trends, the time td also tends to increase as the process exothermicity decreases (not shown), testifying that the amount of externally provided heat also becomes progressively higher. The characteristic temperatures Tmax, Tmaxa, T, Tia, Tconv, Toverh and Tdec and, for comparison purposes, the average heating temperature, TS, are reported versus the sample number in Fig.14 whereas Figure 15 reports the actual conversion interval, tconv, and the overheating interval, toverh. It can be observed that the Tia values are very close to the TS and Tdec values, a further confirmation of the correct detection of the induction time. Apart from the obvious trend and values of Tmax and Tmaxa, the average temperatures Toverh and Tconva are approximately the same (in other words, the average temperature over the intervals tmax-ti and td-tmax is roughly the same) and higher than the average heating temperature (up to about 25-65K). The characteristic time intervals are markedly affected by the global exothermicity of the conversion process, with values that become progressively longer from the first to the second and third group (toverh varies approximately between 140 and 550K and tconv between 560 and 1600s). Having in mind the design effective control systems, the overheating stage is certainly the most critical issue. Hence, an evaluation of the thermal severity and rapidity of the heat release can be made by means of the ratios Toverh/TS, Tmaxa/TS and toverh/ti reported in Fig.15, which can also be used to define the regime of pyrolytic runaway. Similar to the assumptions of a previous study,25 for the thermal aspects, the most critical conditions correspond to the following imposed constraints: Tconv/TS>1 and Tmaxa/TS≥1.2. The first is met by all the samples whereas the second one by all the samples of the first group, characterized by a marked exothermicity, and only a few of the second one. The third constraint (rapidity) required for the pyrolytic runaway is more


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difficult to define as it is expected to be more affected by the sample reactivity and the packed bed properties (for instance, the bulk density). The constraint tca/ti≤0.20, milder than tca/ti≤0.15 imposed for a much more reactive and exothermic waste,25 can be reasonably applied for the residues under study. It can be seen that it is met, together with the temperature constraints, only by the samples of the first group. Therefore, only this group undergoes conversion in a regime of pyrolytic runaway. However, it should be noticed that the behavior of the second feedstock group is also rather critical with Tmaxa/TS between 1.16 and 1.2 and tca/ti between 0.2 and 0.28, that is, the conversion process is still rather exothermic and very rapid. The yields of the lumped product classes and the gaseous species (global mass closure around 95%) are reported versus the sample number in Table 2, including the Tmaxa values. Indeed the product distribution is determined not only by the specific chemico-physical properties of each sample but also by the different thermal conditions actually achieved during conversion. Moreover the char yields, Y773, evaluated at the temperature of 773K from the thermogravimetric curves, already used to introduce the temperature Tdec, are also reported. In this way it is possible to compare the behavior of the different samples under the same thermal conditions, that is, for a conversion process taking place in the presence of negligible spatial gradients (external heat transfer control). Moreover, given the small sample mass and the extremely small particle sizes, it is likely that the char formation mainly results from primary decomposition. In all cases, the Tmaxa values are lower than 773K and therefore the higher amounts of char produced from packed-bed pyrolysis can be attributed to both reduced primary devolatization rates and enhanced secondary condensation rates (longer intra-particle residence times). For the first feedstock group, the differences in the char yields are around 10wt% (average values around 35 and 25wt% for the two experimental systems, respectively). Also the yields of the other two product classes from packed-bed pyrolysis are approximately the same (gas and liquid yields around 11 and 47wt%, respectively). For the other two groups, the char yields increase with the feedstock number for both experimental devices (and conditions) with differences that tend to increase (pistachio shells are again an exception). Therefore, as already reported,31 primary char formation is favored by high contents of extractives/lignin (see Fig. 1A) and, as well known, by low pyrolysis temperatures.4 In fact, the high char yields obtained from beech wood are attributable to the low exothermicity of the process (low Tmaxa value) and not to the microstructure and composition properties. Also, the increasing difference between the yields of the two experimental systems can be justified by the progressively lower Tmaxa values of the packed bed ACS Paragon Plus Environment

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(with respect to the constant value of 773K of the thermogravimetric system). For the packed bed, the increase in the char yields is compensated by a reduction in the yields of the liquid product. The gas yields are approximately constant and essentially consist of CO2 (5-10wt%), CO (1-3wt%) and CH4 (0.8-0.1wt%). It is known that the global exothermicity of the pyrolysis process is mainly a consequence of char formation44-46 independently from the primary or secondary origin, though the magnitude of the relative reaction heats is still unknown. The higher lignin/extractive contents of the residues, with respect to wood, are expected to favor the formation of primary char.31 However, based on the findings of previous studies,

44-46

the exothermicity of biomass pyrolysis appears to be mainly

associated with secondary processes. In fact it is recognized that elevated pressures and long contact times between the organic vapors and the hot char surfaces favor the secondary heterogeneous formation of char.47-49 Having established that the intra-particle contact time is the crucial one (the intra-bed permanence of the vapors is anyway very short16) and that indigenous or added alkali metals catalyze secondary vapor-phase reactions,4 it can be understood that the scarcely porous, relatively thick and alkali-rich shells and stones examined here are prone to significant exothermicity display. Apart from the obvious importance of the size,22 it can also be hypothesized that a higher strength, compared with wood, avoids or reduces structural failure again favoring longer permanence times of the volatiles within the particles. The intra-particle vapor pressure is also expected to depend on the primary decomposition rate of the lignocellulosic substrate, raised by the process exothermicity, whereas the vapor reactivity may depend on the specific composition. Therefore this is an aspect that will need careful investigation in the future. Both vapor pressure and reactivity in their turn are affected by the feedstock chemico-physical properties and the configuration and operating conditions of the conversion device. In this regard, apart from the heating temperature, the external heating rate, that is, the rate of increase of the heating temperature, can also be important for the magnitude of the exothermic display (the experiments discussed here are made by instantaneously exposing the lateral surface of the cylindrical bed to an assigned temperature or radiant heat flux intensity). In quantitative terms, only the half of the samples examined, namely those of the first group, displays the most critical conversion regime. In an attempt to justify the different exothermicity, it can be useful to examine the difference in the properties between this and the other two feedstock groups. The first feedstock group is, on the average, characterized by lower lignin contents, which give rise to higher amounts of volatile products in pyrolysis (as indicated by the lower Y773 values), that is, ACS Paragon Plus Environment

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higher intra-particle vapor pressures (and rates for secondary reactions). It is possible that this effect predominates over the plausibly faster rate of volatile removal from the particles. Also, these samples own medium-high alkali contents and the original particle size (thickness) is always relatively thick (1-4mm), both factors favoring secondary reaction processes. The chemical characterization of the vapor-phase products still needs to be made but it is possible that the reactions of vapors generated from holocellulose, which show a marked tendency toward charring,50 give a more important contribution to exothermicity. On the other hand, despite the high cellulose contents, the thin pistachio shells do not allow for long contact times between vaporphase compounds and char. Moreover it has already been observed25

that the magnitude of the

exothermicity display is affected by the relative values of Ts and Tdec (the latter depends on the feedstock chemical composition and ash chemistry). However, for the samples examined, these differences are not so high (the average decomposition temperature of the first group is 583K versus 587 for the other two groups) as to justify differences in the Tmax values up to about 200K and marked differences in the actual conversion conditions. The results of this study again support the speculation that the exothermicity of biomass pyrolysis is mainly caused by secondary reaction activity but the quantification of the related contribution is still difficult. The development of multi-step or detailed decomposition mechanisms of biomass pyrolysis combined with estimates of the reaction heats, as made by the few attempts in this direction,51,52 certainly

represent a mandatory and preliminary

research activity, before the

formulation and validation of transport models that can be used to interpret the packed-bed data. Finally, it is worth stressing that the heating modality, along the external surface of the particle or the packed bed, and the remarkable mass under play for thick particles or dense-phase pyrolyzers permit an extremely clear display of the exothermic effects. Nevertheless the reaction heat is always very important (i.e. also for lean-phase reactors) in relation to amount of external heat needed not only for feedstock pre-heating but also for the progress of the reaction.11 CONCLUSIONS The packed-bed pyrolysis of a significant number of lignocellulosic residues constituted by nut shells and fruit stones is investigated. Apart from pistachio shells, the feedstock proximate analysis (and ultimate analysis and chemical composition) is similar with FC and lignin/extractive contents higher than those typical of both hardwoods and softwoods. Also, the decomposition temperatures are comparable and generally lower than those of wood. Moreover, contrary to wood, the microstructure, examined by SEM images of chars, is always scarcely porous and essentially ACS Paragon Plus Environment

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consists of a vesicular or a foamed tissue crossed by a very few large vessels hosting bundles of fibers (stones) or elongated rolled elements (shells) of much smaller size. Also, EDX analysis reveals that the deposits, scattered on the char tissue, are rich in minerals including K, Ca, Mg, Na, Si and minor amounts of Al and Fe. The K contents are again much higher than those of wood. In this way the contact time between the vapor-phase decomposition products and the char is extended and the secondary reaction rates are exalted by alkaline catalysis. The moderate heating temperature of the packed bed, around 585K, is comparable with the feedstock decomposition temperatures so that the reaction-induced overheating is clearly visible. The magnitude of the exothermic display is much higher than that of wood but with noticeable differences among the residues. Indeed, the mild external heating conditions result in severe pyrolytic runaway only in several cases when the conversion process becomes very rapid and hardly controllable with overheating intensity approximately corresponding to about 190-230K. These findings further corroborates the importance of the pyrolysis reaction heats in the exploitation of agro-industrial residues. In conclusion, the magnitude of the reaction exothermicity is exalted by factors that favor the occurrence of secondary pyrolysis: a) scarcely porous microstructures, b) remarkable particle thicknesses, preserving the original material structure, c) significant contents of alkali compounds, d) high intra-particle pressures of the organic vapor-phase products and presumably e) good structural integrity during conversion. On the other hand, from the quantitative point of view, despite the close similarity in the physical appearance and microstructure, the size of the particle thickness and chemical composition are crucial factors for the global exothermicity of nut shell and fruit stone pyrolysis. Compared with chemical kinetics and product distributions, the magnitude of the primary and secondary reaction thermicity of biomass pyrolysis is still a scarcely investigated topic. The evidence of the remarkable pyrolysis exothermicity can represent a strong motivation for further investigations in this direction. Supporting Information Description of the bench-scale packed-bed reactor, chemical composition and proximate and ultimate analysis nut shells and fruit stones ACKNOWLEDGMENTS The authors thank Mr. Luciano Cortese (Istituto di Ricerche sulla Combustione, CNR, Napoli, Italy) for the SEM images and the EDX analysis of the samples. ACS Paragon Plus Environment

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REFERENCES [1] Ranzi, E.; Debiagi P. E. A.; Frassoldati, A. Mathematical modeling of fast biomass pyrolysis and bio-oil formation. Note I: kinetic mechanism of biomass pyrolysis. ACS Sustainable Chem. Eng. 2017, 5, 2867−2881. [2] Ranzi, E.; Debiagi P. E. A.; Frassoldati, Mathematical modeling of fast biomass pyrolysis and bio-oil formation. Note II: secondary gas-phase reactions and bio-oil formation. ACS Sustainable Chem. Eng. 2017, 5, 2882−2896. [3] Maduskar, S.; Facas, G. G.; Papageorgiou, C.; Williams, C. L.; Dauenhauer, P. J.; Five rules for measuring biomass pyrolysis rates: pulse-heated analysis of solid reaction kinetics of lignocellulosic biomass. ACS Sustainable Chem. Eng. 2018, 6, 1387−1399. [4] Di Blasi, C. Modeling chemical and physical processes of wood and biomass pyrolysis. Progr. Energ. Combust. Sci. 2008, 34, 47-90. [5] Pecha, M. B.; Garcia-Perez, M.; Foust, T.D.; Ciesielski, P. N. Estimation of heat transfer coefficients for biomass particles by direct numerical simulation using microstructured particle models in the laminar regime. ACS Sustainable Chem. Eng. 2017, 5, 1046−1053. [6] Williams, C. L.; Westover, T. L.; Petkovic, L. M.; Matthews, A.C.; Stevens, D. M.; Nelson, K. R. Determining thermal transport properties for softwoods under pyrolysis conditions. ACS Sustainable Chem. Eng. 2017, 5, 1019−1025. [7] Corbetta, M.; Frassoldati, A.; Bennadji, H.; Smith, K.; Serapiglia, M.J.; Gauthier, G.; Melkior,T.; Ranzi, E.; Fisher E. M.; Pyrolysis of centimeter-scale woody biomass particles: kinetic modeling and experimental validation. Energy Fuels 2014, 28, 3884−3898. [8] Ciesielski, P. N.; Crowley, M. F.; Nimlos, M. R.; Sanders, A. W.; Wiggins, G. M.; Robichaud,D.; Donohoe, B. S.; Foust, T. D. Biomass particle models with realistic morphology and resolved microstructure for simulations of intraparticle transport phenomena. Energy Fuels 2015, 29, 242−254. [9] Xiong Q.; Kong, S.C. High-resolution particle-scale simulation of biomass pyrolysis. ACS Sustainable Chem. Eng. 2016, 4, 5456−5461. [10] Goyal, H.; Pepiot P., On the validation of a one-dimensional biomass pyrolysis model using uncertainty quantification. ACS Sustainable Chem. Eng. 2018, 6, 12153−12165. [11] Di Blasi, C.; Branca, C.; Galgano, A. On the experimental evidence of exothermicity in wood and biomass pyrolysis. Energy Technology 2017, 5, 19-29. [12] Becidan, M.; Skreiberg, O.; Hustad, J. E. Experimental study on pyrolysis of thermally thick biomass residues samples: Intra-sample temperature distribution and effect of sample weight (‘‘scaling effect’’). Fuel 2007, 86, 2754–2760. ACS Paragon Plus Environment

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pyrolysis reactions of ZnCl2-loaded wood. Ind. Eng. Chem. Res. 2015, 54, 12741-12749. [28] Di Blasi, C.; Branca, C.; Galgano, A. Influences of potassium hydroxide on the rate and thermicity of wood pyrolysis reactions.Enery Fuels 2017, 31, 6154-6162. [29] Di Blasi, C.; Branca, C.; Galgano, A. Role of the potassium chemical state in the global exothermicity of wood packed-bed pyrolysis. Ind. Eng. Chem. Res. 2018, 57, 11561-11571. [30] http://waynesword.palomar.edu/ecoph8.htm [31] Di Blasi, C.; Branca, C.; Galgano, A. Biomass screening for the production of furfural via thermal decomposition. Ind. Eng. Chem. Res. 2010, 49, 2658-2671. [32] Branca, C.; Di Blasi, C.; Galgano, A.; Pyrolytic conversion of wastes from cereal, protein and oil-protein crops. J. Analyt. Appl. Pyrolysis 2017, 127, 426-435, 2017. [33] Petterson, R.C. The chemical composition of wood. In: Rowell, R. (Ed.), Chemistry of Solid Wood, Adv. Chem. Series 207. American Chemical Society, Washington, DC, 1984, pp. 57–126. [34] Buekens, A. G.; Bridgwater, A. V.; Ferrero, G. L.; Maniatis, K. Commercial and marketing aspects of gasifiers; EUR 12736; Commission of the European Communities: Bruxelles, Belgium, 1990. [35] Varhegyi, G.; Gronli, M. G.; Di Blasi, C. Effects of sample origin, extraction and hot water washing on the devolatilization kinetics of chestnut wood. Ind. Eng. Chem. Res. 2004, 43, 23562367. [36] Heschel, W.; Klose, E., On the suitability of agricultural by-products for the manufacture of granular activated carbon. Fuel 1995, 74, 1786-1791. [37] Mettler, M. S.; Vlachos, D. G.; Dauenhauer, P. J. Top ten fundamental challenges of biomass pyrolysis for biofuels, Energy Environ. Sci. 2012, 5, 7797−7809. [38] Kersten, S.; Garcia-Perez, M. Recent developments in fast pyrolysis of ligno-cellulosic materials. Curr. Opin. Biotechnol. 2013, 24, 414–420. [39] Haas, T. J.; Nimlos, M. R.; Donohoe, B. S. Real-time and post-reaction microscopic structural analysis of biomass undergoing pyrolysis. Energy Fuels 2009, 23, 3810–3817. [40] Demiral, H.; Baykul, E.; Gezer, M. D.; Erkoç, S.; Engin A.; Baykul, M. C. Preparation and characterization of activated carbon from chestnut shell and its adsorption characteristics for lead. Sep. Sci. Technol. 2014, 49, 2711-2720. [41] Haykiri-Acma, H.; Yamana, S.; Kucukbayrak, S.; Morcali, M. H. Does blending the ashes of chestnut shell and lignite create synergistic interaction on ash fusion temperatures? Fuel Proc. Technol. 2015, 140, 165–171. [42] Vassilev S. V.; Baxter D.; Andersen L. K.; Vassileva C. G.; An overview of the chemical ACS Paragon Plus Environment

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composition of biomass. Fuel 2010, 89, 913–933. [43] Di Blasi, C. Influences of model assumptions on the predictions of cellulose pyrolysis in the heat transfer controlled regime. Fuel 1996, 75, 58-66. [44] Rath, J.; Wolfinger, M. G.; Steiner, G.; Krammer, G.; Barontini, F; Cozzani, V. Heat of wood pyrolysis. Fuel 2003, 82, 81-91. [45] Gomez, C.; Velo, E.; Barontini, F.; Cozzani, V. Influence of secondary reactions on the heat of pyrolysis of biomass. Ind. Eng. Chem. Res. 2009, 48, 10222-10233. [46] Basile, L.; Tugnoli, A.; Tramigioli, C.; Cozzani, V. Thermal effects during biomass pyrolysis. Thermochim. Acta 2016, 636, 63-70. [47] Wang, L.; Trninic, M.; Skreiberg, O.; Gronli, M.; Considine, R.; Antal, M. J. Is elevated pressure required to achieve a high fixed-carbon yield of charcoal from biomass? 1. Round Robin results for three different corncob materials. Energy Fuels 2011, 25, 3251-3265. [48] Manyà, J. J., Azuara, M.; Manso, J. A., Biochar production through slow pyrolysis of different biomass materials: seeking the best operating conditions. Biomass Bioenergy 2018, 117, 115–123. [49] Legarra, M.; Morgan, T.; Turn, S.; Wang, L.; Skreiberg, Ø.; Antal, M. J. Carbonization of Biomass in Constant-Volume Reactors. Energy Fuels 2018, 32, 475−489. [50] Branca, C.; Di Blasi C.; Elefante, R. Devolatilization of conventional pyrolysis oils generated from biomass and cellulose. Energy Fuels 2006, 20, 2253-2261. [51] Branca, C.; Di Blasi, C. A summative model for the pyrolysis reaction heats of beech wood. Thermochim. Acta 2016, 638,10-16. [52] Anca-Couce , A.; Robert Scharler, R. Modelling heat of reaction in biomass pyrolysis with detailed reaction schemes. Fuel 2017, 206, 572–579. FIGURE CAPTIONS Figs.1A-1C - Chemical composition (A, average literature values), proximate analysis (B) and ultimate analysis (C, Ref. [36]) of nut shells and fruit stones. Figs. 2A-2D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): cross sections of hazelnut and macadamia nut shells (A,B) and olive (C) and nectarine (D) stones (the colored arrows indicate large (green), thin (yellow) or rolled (pink) hollow fibers). Figs. 3A-3D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): cross sections of apricot (A), prune (B) and cherry (C) stones and peanut shell (C) (the colored arrows indicate large (green) or thin (yellow) hollow fibers). ACS Paragon Plus Environment

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Figs. 4A-4D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the cross sections of nectarine (A (foamed tissue), B (large and thin hollow fibers)) and prune (C (foamed tissue), D (thin hollow fibers)) stones (the yellow arrows indicate thin hollow fibers). Figs. 5A-5D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the cross sections of almond (A) and peanut (B) shells and rolled elements placed inside the large vessels of macadamia (C) and Brazil (D) nut shells (the colored arrows indicate large (green) or thin (yellow) hollow fibers). Figs. 6A-6D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the cross sections of walnut (A) and coconut (B) shells and cross sections of pistachio (C) and pine nut (D) shells (the colored arrows indicate large (green) or thin (yellow) hollow fibers). Figs. 7A-7D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the surfaces of olive (A) and cherry (B) stones and pistachio (C) and Brazil nut (D) shells (arrows indicate the deposits on the surfaces). Fig.8 - Temporal profiles of the average temperature of the packed bed, Ta, during pyrolysis of nut shells and fruit stones (average heating temperature Ts=585K). Fig.9 - Radial profiles of the packed-bed temperatures at the time tmax (listed in the plot), corresponding to the attainment of the maximum temperature, for nut shells and fruit stones (average heating temperature Ts=585K). The average steady temperature profile of the charred residue, Tchar, is also reported (dashed line). Figs.10A-10D - Radial profiles of the packed-bed temperature for several times for peach stones (A), almond shells (B), Brazil nut shells (C) and Macadamia nut shells (D) (average heating temperature Ts=585K). The steady temperature profile of the charred bed, for each sample, is indicated with a dashed line. Fig.11 - Radial profiles of the packed-bed temperature at the induction (or preheating) time ti (listed in the plot) for nut shells and fruit stones (average heating temperature Ts=585K) with the indication (void circles) of the trigger point. Fig.12 - Temporal profiles of the rate of gas release (the time derivative of the percentage of gas released) from the packed bed during pyrolysis of nut shells and fruit stones (average heating temperature Ts=585K). Fig. 13 -Temperature (center bed temperature, Tc, and average bed temperature, Ta) versus time profiles (yellow peach stones) with the graphical representation of several process parameters: the maximum average temperature, Tmaxa, at the time tmax corresponding to the maximum temperature, Tmax, (and related maximum overshoot, T), the average spatial temperature at the induction time, Tia, the average temperatures Toverh and Tconv, referred to the actual overheating and conversion intervals, toverh = tmax-ti and tconv=td-ti , the induction time, ti, and the decay time, td. ACS Paragon Plus Environment

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Fig.14 - Average spatial temperature, Tmaxa, corresponding to time, tmax, when the maximum temperature is attained, average spatial temperature at the induction time, Tia, average temperatures referred to the actual overheating and conversion intervals, Toverh and Tconv, maximum temperature, Tmax, maximum temperature overshoot, T, sample decomposition temperature, Tdec, and average heating temperature, TS, versus the sample number (average heating temperature TS=585K). Fig.15 - Actual overheating and conversion intervals, toverh and tconv, and ratios toverh /ti, Toverh/TS, and Tmaxa/TS (ti is the induction time and TS the average heating temperature) versus the sample number (average heating temperature Ts=585K). Table 1 - Initial sample mass, M0, size of the particle thickness, , and decomposition temperature, Tdec, (this corresponds to the release of 50wt % of the total volatiles as measured from thermogravimetric curves at 5K/min). Table 2 - Average spatial temperature, Tmaxa, corresponding to time, tmax, when the maximum temperature is attained, percent of the solid mass fraction detected at 773K from thermogravimetric curves at 5K/min, Y773, yields of char, liquids, gas and gas components from the packed pyrolysis, expressed as percent of the initial dry mass (average heating temperature Ts=585K).


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Figs.1A-1C - Chemical composition (A, average literature values), proximate analysis (B) and ultimate analysis (C, Ref. [36]) of nut shells and fruit stones. ACS Paragon Plus Environment

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Figs. 2A-2D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): cross sections of hazelnut and macadamia nut shells (A,B) and olive (C) and nectarine (D) stones (the colored arrows indicate large (green), thin (yellow) or rolled (pink) hollow fibers).


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Figs. 3A-3D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): cross sections of apricot (A), prune (B) and cherry (C) stones and peanut shell (C) (the colored arrows indicate large (green) or thin (yellow) hollow fibers).


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Figs. 4A-4D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the cross sections of nectarine (A (foamed tissue), B (large and thin hollow fibers)) and prune (C (foamed tissue), D (thin hollow fibers)) stones(the yellow arrows indicate thin hollow fibers).


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Figs. 5A-5D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the cross sections of almond (A) and peanut (B) shells and rolled elements paced inside the large vessels of macadamia (C) and Brazil (D) nut shells (the colored arrows indicate large (green) or thin (yellow) hollow fibers).


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Figs. 6A-6D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the cross sections of walnut (A) and coconut (B) shells and cross sections of pistachio (C) and pine nut (D) shells (the colored arrows indicate large (green) or thin (yellow) hollow fibers).


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Figs. 7A-7D - SEM images of chars from packed-bed pyrolysis (average heating temperature Ts=585K): parts of the surfaces of olive (A) and cherry (B) stones and pistachio (C) and Brazil nut (D) shells (arrows indicate the deposits on the surfaces).


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Fig.8 - Temporal profiles of the average temperature of the packed bed during pyrolysis of nut shells and fruit stones (average heating temperature Ts=585K).


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Fig.9 - Radial profiles of the packed-bed temperatures at the time tmax (listed in the plot), corresponding to the attainment of the maximum temperature, for nut shells and fruit stones (average heating temperature Ts=585K). The average steady temperature profile of the charred residue, Tchar, is also reported (dashed line).


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Figs.10A-10D - Radial profiles of the packed-bed temperature for several times for peach stones (A), almond shells (B), Brazil nut shells (C) and Macadamia nut shells (D) (average heating temperature Ts=585K). The steady temperature profile of the charred bed, for each sample, is indicated with a dashed line.


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Fig.11 - Radial profiles of the packed-bed temperature at the induction (or preheating) time ti (listed in the plot) for nut shells and fruit stones (average heating temperature Ts=585K) with the indication (void circles) of the trigger point.


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Fig.12 - Temporal profiles of the rate of gas release (the time derivative of the percentage of gas released) from the packed bed during pyrolysis of nut shells and fruit stones (average heating temperature Ts=585K).


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Fig. 13 -Temperature (center bed temperature, Tc, and average bed temperature, Ta) versus time profiles (yellow peach stones) with the graphical representation of several process parameters: the maximum average temperature, Tmaxa, at the time tmax corresponding to the maximum temperature, Tmax, (and related maximum overshoot, T), the average spatial temperature at the induction time, Tia, the average temperatures Toverh and Tconv, referred to the actual overheating and conversion intervals, toverh = tmax-ti and tconv=td-ti , the induction time, ti, and the decay time, td.


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Fig.14 - Average spatial temperature, Tmaxa, corresponding to time, tmax, when the maximum temperature is attained, average spatial temperature at the induction time, Tia, average temperatures referred to the actual overheating and conversion intervals, Toverh and Tconv, maximum temperature, Tmax, maximum temperature overshoot, T, sample decomposition temperature, Tdec, and average heating temperature, TS, versus the sample number (average heating temperature TS=585K).


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Fig.15 - Actual overheating and conversion intervals, toverh and tconv, and ratios toverh /ti, Toverh/TS, and Tmaxa/TS (ti is the induction time and TS the average heating temperature) versus the sample number (average heating temperature Ts=585K).


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N.

Biomass

M0 [g]

τ [mm]

Tdec [K]

1

Hazelnut shells

27.0

1-2

592

2

Walnut shells

29.1

1-2

582

3

Yellow peach stones

28.8

2-3

585

4

Cherry stones

28.9

1-1.5

591

5

Almond shells

28.1

1-3

574

6

Olive stones

31.0

1-2

573

7

Nectarine stones

29.2

2-2.5

587

8

Apricot stones

25.8

2-4

581

9

Pine nut shells

28.1

1-2

600

10

Plum stones

28.8

1-2

588

11

Brazil nut shells

24.7

1-2

587

12

Coconut shells

28.4

3-4

575

13

Peanut shell pellets

25.8

1

587

14

Macadamia nut shells

29.4

2-4

597

15

Pistachio shells

29.8

1

584

16

Chestnut shell pellets

26.4

0.5-1

580

17

Beech wood pellets

28.0

1-2

592

Table 1 - Initial sample mass, M0, size of the particle thickness, , and decomposition temperature, Tdec, (this corresponds to the release of 50wt % of the total volatiles as measured from thermogravimetric curves at 5K/min).


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Tmaxa [K]

Y773 [wt%]

Char [wt%]

Liquids [wt%]

Gas [wt%]

CO2 [wt%]

CO [wt%]

CH4 [wt%]

Hazelnut shells

765

25.8

36.42

47.71

11.39

7.87

2.70

0.62

2

Walnut shells

760

24.5

33.81

48.49

12.26

8.61

3.16

0.32

3

Yellow peach stones

746

25.0

37.81

48.16

9.22

6.41

2.26

0.46

4

Cherry stones

744

23.4

36.73

47.75

11.03

7.34

2.81

0.76

5

Almond shells

734

23.4

33.75

47.67

12.76

9.04

3.2

0.38

6

Olive stones

732

27.8

37.14

44.26

14.01

10.23

3.2

0.41

7

Nectarine stones

729

23.4

40.31

46.14

9.12

6.42

2.18

0.42

8

Apricot stones

717

21.9

34.95

48.51

10.5

7.24

2.70

0.40

9

Pine nut shells

703

26.9

42.20

41.53

11.81

8.22

3.1

0.39

10

Plum stones

697

19.6

37.36

46.72

11.45

8.17

2.6

0.52

11

Brazil nut shells

691

34.1

49.76

37.88

7.85

6.08

1.45

0.17

12

Coconut shells

688

25.3

38.96

46.44

8.82

6.41

2.13

0.21

13

Peanut shell pellets

681

29.1

41.69

41.27

12.16

9.38

2.60

0.16

14

Macadamia nut shells

652

24.8

47.21

40.43

7.41

5.58

1.68

0.10

15

Pistachio shells

646

12.9

34.46

51.34

8.96

6.51

2.28

0.12

16

Chestnut shell pellets

627

37.7

57.28

30.83

7.37

6.26

1.09

0.01

17

Beech wood pellets

620

25.8

41.55

44.12

8.66

6.28

2.31

0.05

N.

Biomass

1

Table 2 - Average spatial temperature, Tmaxa, corresponding to time, tmax, when the maximum temperature is attained, percent of the solid mass fraction detected at 773K from thermogravimetric curves at 5K/min, Y773, yields of char, liquids, gas and gas components from the packed pyrolysis, expressed as percent of the initial dry mass (average heating temperature Ts=585K).


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For Table of Contents Use Only

Biomass pyrolysis can be a highly exothermic process. A better understanding of these aspects can enhance the exploitation of sustainable bio-fuels and green chemicals.


39

Exothermic Events of Nut Shell and Fruit Stone ... - ACS Publications

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