Characterization of Colombian Agroindustrial Biomass Residues as

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Characterization of Colombian agroindustrial biomass residues as energy resources Gloria Marrugo, Carlos F. Valdés, and Farid Chejne Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b01596 • Publication Date (Web): 08 Sep 2016 Downloaded from http://pubs.acs.org on September 9, 2016

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Characterization of Colombian agroindustrial biomass residues as energy

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resources

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Gloria Marrugoa, Carlos F. Valdésa, Farid Chejnea,1

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Universidad Nacional de Colombia, Mines Faculty, Processes and Energy School, TAYEA Group, Carrera 80 No. 65-223, Medellin (Colombia).

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Abstract:

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A physical and chemical characterization of three Colombian agricultural biomass residues

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was carried out to identify promising feedstocks for thermochemical energy production.

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The three chosen were sugarcane bagasse (SCB), rice husk (RH) and palm kernel shell

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(PKS). Results showed that SCB, has high volatile material (87.41 wt.% daf),

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lignocellulosic composition high in hemicellulose (29.68 wt.% daf) and cellulose (39.81 wt.

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daf), high alkali index (4.07) and soft morphology; these characteristics make it a good

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candidate for fast pyrolysis to produce bio-oil and gas. The RH, despite having a

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lignocellulosic composition similar to SCB, has slightly less volatile matter than SCB

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(75.73 wt.% daf), a soft morphological structure, and high ash content (19.33 wt.%) mainly

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of non-catalytic species these characteristics make RH unattractive for pyrolysis; however,

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its fixed carbon content makes it very interesting for combustion and gasification processes.

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On the other hand, the PKS is the biomass with the highest content of fixed carbon (22.78

Corresponding author at: Universidad Nacional de Colombia, Facultad de Minas, Escuela de Procesos y Energía, Medellín, Colombia. Email address: [email protected]

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wt.% daf) and lignin (58.30 wt.%); its hard structure, low ash content (2.67 wt.%), and high

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lignin content make it most suitable for high temperature processes like combustion and

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gasification processes.

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Keywords: Sugarcane bagasse, rice husk, palm kernel shell, characterization,

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morphological structure.

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1. Introduction

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Energy supply is one of the greatest concerns in modern society. The demand for energy

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has driven rapid growth of the use of fossil fuels, depleting the supply and the raising the

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cost of energy in many places1,2. Additionally, burning fossil fuels releases greenhouse

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gases that have been blamed for climate change3. With this in mind, traditional

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technologies are not sustainable. Today there are great efforts to develop renewable and

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efficient energy production processes. The use of biomass is generally considered a

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sustainable replacement or partial substitution for fossil fuels since it has a net-neutral

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production of carbon dioxide.

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The term “biomass” includes all existing organic matter which is biodegradable and not

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fossilized. For energy production, there are several sources known to be good feedstocks:

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wood, short-cycle crops, green waste, forest residues, and agricultural residues.

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Agricultural residues have been heavily studied for energy generation. Besides their

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environmental benefits as part of the carbon cycle, it is ensured an economic valuation, they

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are already part in profitable business models4. In a country like Colombia, high agro-

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industrial activity has created a large supply of available biomass that can satisfy the

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demand for sustainable energy if forestry and agricultural residues are managed well5.

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Around 72 million ton/year of agricultural residual biomass is thought to exist, indicating

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an energy potential of around 332,000 TJ/year. A recent study estimates the production of

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sugarcane bagasse at 7 million tons/year, rice husks at 453,000 ton/year, and palm oil

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residues at 1.6 million ton/year in Colombia6.

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To use biomass as an energy resource, it needs to be processed. There are physical

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processes such as extraction oils, biological processes such as the anaerobic digestion for

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the production of biogas, and thermochemical processes that provide multiple and complex

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products in short reaction times7. Among the thermochemical processes, we find pyrolysis,

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gasification, and combustion. Pyrolysis and gasification have been heavily researched in

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the last twenty years which has allowed for the use of biomass in applications at small and

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medium levels for power and thermal energy production4.

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Biomass comes from various croplands and species and all plants have different chemical

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compositions 8,9. Thus, it is necessary to carry out fundamental studies on the impacts of

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these features on energetic processes. Despite a great deal of information published

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regarding good use of biomass, studies with detailed characterizations are scarce and are

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limited to databases available from organizations such as the National Renewable Energy

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Laboratory (NREL)10, and Deutsches Biomasse Forschungs Zentrum (DBFZ). The reports

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are normally limited to proximate analysis, ultimate analysis, and energy content11–13.

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Lignocellulosic characterization is important for knowing the effects of composition on

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reaction kinetics9,14,15 and other process parameters9 during thermochemical conversion.

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Characterization tools such as XRD (X-ray diffraction), XRF (X-ray fluorescence), SEM

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(scanning electron microscopy), and gas adsorption studies provide the surface area and

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morphological structure. Many studies present this information in an isolated form or with

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a very specific purpose15–20 Combining all available information is critical to fully

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understand the phenomena that control energy production processes.

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In this manuscript, the authors present full physicochemical characterizations for three

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relevant Colombian agro-industrial biomasses: sugar cane bagasse, rice husk, kernel palm

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shell. Lignocellulosic composition and XRD analyses are presented as tools to assess the

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influence that the lignocellulosic components have on thermochemical conversion. XRF

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analysis was performed to quantify metallic species, making use of the alkali index. BET

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surface area was determined and morphological properties were studied via optical

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microscopy (transmitted and reflected). Combination of this data led to conclusions

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regarding the catalytic reactivity of the surface of the biomass. The authors propose that

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these characterizations are fundamental tools for the qualification and quantification of the

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effects of a biomass’ structure and physiochemical composition on thermochemical

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processes such as pyrolysis, gasification, and combustion.

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2. Materials and methods

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2.1

Biomass selection, characterization and preliminary preparation

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For the selection of biomasses for this study, several criteria were taken into consideration.

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In the literature it is common to limit this election to abundance and availability. In

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Colombia where there is a wide variety of agro-industrial materials, this criteria does not

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refine the selection to the requirements of the end use, like in the most of the cases21; the

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operability and process yields are dependent on the feedstock selected. In this study, three

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Colombian agro-industrial residues were selected, taking into consideration availability,

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energy content, and of course differences in its physicochemical characteristics in order to

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predict their behaviors in thermochemical transformation processes.

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Once selected, a general characterization of the samples was carried-out as they were

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received; sampling and quartering was performed to obtain a characteristics and

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representatives samples. Apparent density was determined making use of a graduated

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cylinder and the weight of the material in a certain volume. Moisture content was

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measuring by using a halogen moisture balance (Metter Toledo HB43-S) with a heating

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method programmed up to 110°C and holding at this temperature, until ensuring an

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unchanging weight. Later, biomass samples were subjected to the preparation process that

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included solar drying, grinding with a hammer mill at 6500 rpm, and classification of

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particle size using ASTM E11-87 series sieves, defined by the ranges -12/+20

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(average/diameter, Dp,m = 1.27 mm), -20/+30 (Dp,m = 0.73 mm) and passing mesh 30

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(Dp,m < 0.60 mm).

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2.2

Physicochemical biomass characterization methodologies

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Due to the inherent compositional and structural complexity of the biomass, a complete

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characterization of the biomass through multiple analyses is fundamental; this will allow

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researchers to establish relations between its characteristics and the behavior during

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thermochemical energy production processes. Analyses were performed on biomass after

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drying and size reduction.

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The particle analysis was done with the morphological structure features of each biomass

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through optic microscopy with light transmitted/reflected (OM) as well as scanning

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electron microscopy (SEM). Using these techniques it was possible to determine the effect

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of milling on the destruction of basic structures of the biomasses. For the selection of a

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distribution of particle size it is important to consider the type of technology to use.

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2.2.1

Proximate analysis, calorific value and ultimate analysis

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The proximate analysis methods included: moisture (ASTM D3173-11), ash (ASTM

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D3174-12), volatile matter (ASTM D3175–11), and fixed carbon (ASTM D3172)22. For the

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high heating value (PCS or HHV) the procedures describe in ASTM D5865-13 guidelines

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were used. The determination of the C, H, N, content was carried-out using guidelines

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ASTM D5373-14, and sulfur with ASTM D4239-14 Method A and finally the oxygen

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content was determined by difference (subtracting from 100% of the CHNS content and the

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ash content).

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2.2.2

Lignocellulosic compositional analysis

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The content of cellulose, hemicellulose, and lignin present in the biomass was measured

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following NREL/TP-510-42618. Additionally, the content of total solids (NREL/TP-510-

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42621) and ash (NREL/TP-510-42622) were determined23.

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2.2.3

Ash speciation analysis

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The biomass ash characterization allows us to identify mineral species present in the form

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of oxides. The analysis was carried-out with a X-ray fluorescence spectrometer (Thermo

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Model OPTIM’X). The biomasses were size reduced to 250 microns and calcinated at

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750°C for one hour. Then, the ashes were used for the quantification of minerals, which

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allow the identification of nearly 100% of the mineralogical composition of calcinated

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residue.

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2.2.4

BET area and microporosity

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The determination of the surface area was done by absorption of N2 at different pressure

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levels in a Micrometrics TriStar II Plus. The samples were vacuum de-gassed at 150°C for

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24 hours before the analysis in order to remove moisture. The total surface area was

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calculated using the BET multi-layer absorption model24. Similarly, the smallest

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microporosity of biomass was analyzed by CO2 adsorption using the Dubbini - Astakhov

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model25.

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2.2.5

FTIR analysis

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Identification of the main functional groups present in the structure of the biomass was

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carried-out using a Fourier transformed infrared spectrometry (FTIR) in a Perkin Elmer

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Spectrum Two device. With the infrared spectrum, functional groups were identified and

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differences between biomass species were established.

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2.2.6

X-Ray Diffraction (XRD)

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Biomass samples were analyzed in an X-ray diffractometer (Bruker AXS, Cu-kα to 40 kV

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and 30 mA). The measures were taken from an initial angle of 2θ = 5° to a final angle of

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90°. With this technique, we can determine the crystallinity of the lignocellulosic biomass.

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The degree of crystallinity represents the relative amount of crystalline cellulose. It is

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strongly influence by the composition of the biomass, since the relative amount of lignin,

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hemicellulose, and cellulose varies between biomasses19. The crystallinity index (ICr) was

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obtained between the intensity of the peak of 002 (I200, 2θ = 22.5°) and the minimum

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intensity (Iam, 2θ = 18°), according to the formula used by the Segal Method26 in Eq. 1:

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ICr =

(I − I ) x100 I

Eq.1

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2.2.7

Optical Microphotography

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A characterization of the physical structure of the biomass was carried-out with a particle

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size of 1.00, 0.73 y hemicellulose), their physical structures are quite different; the SCB

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appears in the form of thin fibers while the RH is in the form of sheets covered by a cuticle

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that makes them brittle to the touch.

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The RH has less cellulose and a little more lignin than the SCB. The content of

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hemicellulose is lowest for PKS (14.63 wt.% daf) and higher for SCB and RH (~25 wt.%

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daf). The proportions of these components are similar to those presented in the studies

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reported for the SCB, the RH and the PKS, see Table 3.

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Table 3. Physicochemical characterization of biomasses from different countries Biomass

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Origen VM FC A C S O Hem Cel Lig In this study 87.47 12.59 12.34 51.34 0.14 50.68 14.63 53.18 32.19 Malaysia39 81.32 25.27 3.00 45.10 0.04 49.20 Pakistan40 85.97 14.03 5.20 46.19 45.74 South Africa41 81.20 18.80 5.30 50.30 0.07 43.10 Morocco42 88.72 11.28 2.70 52.99 49.92 Brazil43 1.44 26.83 41.38 31.79 Florida44 83.43 16.57 1.60 49.60 43.90 Brazil45 20.90 29.91 42.98 27.11 SCB Indonesia46 83.83 16.17 2.10 51.71 42.64 General mean47 4.5-9 27-32 32-34 19-24 Colombia. Valle48 90.86 9.14 3.90 51.29 0.10 47.72 32.99 43.55 21.76 Malaysia49 57.03 42.97 10.20 42.80 0.03 47.10 30.67 40.00 29.33 Bombay. India50 84.20 2.90 45.11 48.51 27.50 50.20 22.30 California. EEUU51 87.75 12.25 2.44 49.86 0.04 43.58 India52 92.13 7.87 6.00 47.19 0.02 57.46 India. Mathura53 88.78 11.22 4.40 50.47 1.24 35.67 24.04 47.04 28.92 In this study 75.73 24.27 19.33 45.93 0.16 55.97 24.50 39.65 35.84 Thailand54 73.45 26.55 14.00 50.20 0.08 42.80 India55 88.65 11.33 19.36 49.90 52.25 Asia56 5.98 68.64 25.39 India. Mathura53 87.91 12.09 17.40 54.67 0.34 30.76 18.76 43.72 37.52 Uganda. Mean57 79.39 20.62 21.98 40.88 0.03 51.99 18.00 23.80 58.30 RH Brazil58 82.19 17.81 13.00 48.94 0.00 37.47 Canada59 83.00 17.00 20.00 47.00 0.04 45.70 29.00 42.14 28.86 China60 80.38 19.64 17.09 50.47 64.52 Bombay. India50 81.60 23.50 50.85 41.83 34.80 44.80 20.40 California. EEUU51 79.66 20.34 20.26 48.70 0.06 44.48 Colombia59 79.73 20.30 17.89 51.76 0.60 44.09 39.04 22.80 In this study 77.22 22.78 2.67 51.27 0.16 50.55 27.06 14.64 58.30 Netherlands61 81.47 18.54 5.14 50.96 0.27 39.47 Nigeria62 8.68 54.52