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Hindawi International Journal of Forestry Research Volume 2020, Article ID 3457396, 8 pages https://doi.org/10.1155/2020/3457396 Research Article Evaluation of Elemental and Chemical Compositions of Some Fuelwood Species for Energy Value 1,2 1 1 1 2 A. M. Dadile , O. A. Sotannde, B. D. Zira, M. Garba, and I. Yakubu Department of Forestry and Wildlife, Faculty of Agriculture, University of Maiduguri, Maiduguri, Borno State, Nigeria Department of Forestry and Wildlife Management, Faculty of Agriculture, Federal University Gashua, Gashua, Yobe State, Nigeria Correspondence should be addressed to A. M. Dadile; firstname.lastname@example.org Received 9 March 2020; Revised 15 June 2020; Accepted 23 June 2020; Published 27 July 2020 Academic Editor: Nikolaos D. Hasanagas Copyright © 2020 A. M. Dadile et al. )is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Fuelwood species are a crucial part of the ecosystem; they provide energy for cooking, heating, and lightening for both domestic and industrial uses. As a result of their value, there is a need for frequent evaluation of elemental and chemical compositions for management and conservation purposes. Since fuelwood is the most common and cheapest source of energy in both rural and urban areas in northern Nigeria, the study area is facing serious challenges due to indiscriminate felling of trees for energy use, irrespective of species quality for combustion. )erefore, ten fuelwood species were selected for this study. )e selected trees were harvested at Dbh level, replicated three times. Four fuel materials were obtained from each tree sample; these include wood without bark (100% wood sample), wood with 5% bark inclusion, wood with 10% bark inclusion, and whole bark samples and they were evaluated for their inherent elemental and chemical compositions by employing ASTM and TAPPI methods. )e results showed that there were signiﬁcant diﬀerences in the tree species and fuel material types obtained from all the ten fuelwood species used. )e results of carbon content ranges from 49.54% in A. sieberiana to 50.98% in A. leiocarpus. Meanwhile, the addition of 5% and 10% bark reduces carbon content of wood by 1.25% and 2.74%, respectively. Nitrogen content ranged from 0.31% in A. leiocarpus to 1.00% in A. sieberiana. Among the fuel materials used, isolated bark contained approximately 0.45% nitrogen content compared with wood without bark. Among the tree species, hydrogen content ranged from 3.99% in P. reticulatum to 4.66% in C. arereh. )e variation in sulphur contents ranged from 0.24% in C. arereh to 0.93% in A. sieberiana. Lignin content ranged from 10.68% in A. sieberiana to 25.39% in A. leiocarpu and extractive content values ranged from 7.31% in A. leiocarpus to 19.33% in P. reticulatum. Meanwhile, the fuelwood species observed in this study with higher percentage of carbon, hydrogen, and lignin and lower nitrogen and sulphur and extractive content possessed quality fuel value and thereby were encouraged to be incorporated in fuelwood plantation establishment programs (A. leiocarpus, C. molle, C. arereh, and B. aegyptiaca). Lower energy fuelwood species should be allowed for environmental amelioration and carbon sequestration. However, bark contents should be removed for better heating and low ash production during combustion. always increasing due to population size, accessibility, and 1. Introduction being cheaper in price compared with other sources of Ten fuelwood species were selected for the study to inves- energy such as kerosene, electric devices, and LPGs. )ese tigate their inherent fuel quality in relation to nutrient el- are some of the reasons that the majority of the inhabitants ement and chemical composition. )e selection was done prefer fuelwood as a source of energy, and the demand is so based on the demand by the inhabitants and overexploi- high to the extent that the woodland areas are turning to tation of fuelwood species in the northern part of Nigeria. desert areas. Since the northern part of Nigeria is worst hit )is requires a serious need to address the mode of utili- with the fuelwood scarcity, eﬀort must be made to ensure zation of fuelwood species in the region, in that the region is fuelwood selection and create a fuelwood establishment faced with scarce vegetation, and the demand for fuelwood is program based on the fuel quality of the candidate trees. To 2 International Journal of Forestry Research achieve this, it is important to characterize fuelwood species following samples were created using Nosek et al.’s in terms of combustion properties. )e ultimate analysis method : (nutrient elements) plays a vital role in determining the fuel 100%W � wood sample without bark value of any woody biomass. )is is as a result of the strong 5%B � wood samples with 5% bark relationship between them and fuelwood properties. As a ﬁrst guide therefore, the knowledge of the fuelwood prop- 10%B � wood samples with 10% bark erties will help to determine the inherent fuel energy po- 100%B � samples with 100% bark tentials of some tree species. Samples with 5% and 10% bark chips were created by Moreover, the trend in fuelwood demand increases mixing wood sample without bark with the bark sample. )e on a daily basis, and many inhabitants depend on proportion of 5% and 10% were employed due to the high fuelwood for livelihood sustenance. )is increases the numbers of fuelwood with bark contents in the range of 5% quantity and intensity of fuelwood use, with a trend that to 10%, based on the results of various works [10, 11]. Each does not appear to have the possibility of meeting the sample was air-dried at room temperature to constant increasing demand in the future [1–5]. )ese projected moisture content before grinding to a fraction size less than future increases are perhaps because of the unpredictable 1 mm based on the American Standard for Testing and changes in demographic and socioeconomic character- Material (ASTM) standard designation D2013-86 and istics including the interplay between poverty, pop- thereafter subjected to nutrient element and chemical ulation increase, and other factors in this area coupled composition analyses. with the unpredictable ﬂuctuations in the prices of do- mestic fossil fuels as kerosene, liqueﬁed petroleum gas, and others . Meanwhile, such an increase in fuelwood 2.2. Determination of Carbon, Hydrogen, and Oxygen (C-H- demand resulted in deforestation and sand dunce in the O). )e percentages of carbon, hydrogen, and oxygen were area. )erefore, it is important to evaluate chemical and determined by elemental composition such as carbon, hydrogen, oxy- gen, sulphur, and nitrogen to determine the desirable C � 0.637FC + 0.455VM, and quality fuelwood species as a source of energy for both domestic and industrial uses . Proper evaluation H � 0.052FC + 0.62VM, (1) of these properties consequently enhances the overall O � 0.304FC + 0.476VM. wood biomass quality for heating and combustion eﬃ- ciency . Sulphur (S) was obtained using )e objectives of this study are to determine the nutrient elements and chemical composition required for quality S � H + C + O − 100, (2) fuelwood species. )is plays a vital role in assessing fuel value of any woody biomass. As a ﬁrst guide therefore, the knowledge of nutrient properties of fuelwood species will where C is the carbon content, H is the hydrogen content, O help determine the inherent fuel energy potentials of tree is the oxygen content, FC is the percentage of ﬁxed carbon species. and VM is the volatile matter content (ASTM  and Bailey and Blankehorn ). 2. Materials and Methods 2.3. Nitrogen Determination. Nitrogen content was de- )e materials used for the study are ten (10) selected termined using Kjeldahl method adopted from Bremner fuelwood species, digital weighing balance (Metriz 235), . Two grams of wood samples was heated with 100 ml atomic absorption spectrometer, Spectrometer (UV 2150), of distilled water and 20 ml sulphuric acid at 337 C to oven, and platinum crucibles, and Wiley Mill. liberate the reduced nitrogen as ammonium sulfate. One gram of potassium sulfate was added to increase the ° ° boiling point to 373 C. )e mixture heated at 373 C 2.1. Preparation of Wood Samples. Fuelwood species were became very dark colored and gradually became clear identiﬁed 10–15 kilometers away from Damaturu, Yobe and colorless. )en, the solution was distilled with a State, Nigeria, and harvested at 25 cm below and above small quantity of sodium hydroxide, which converted diameter at breast height (Dbh), thereby making a total ammonium to ammonia. )e amount of ammonia and of 50 cm billets, and replicated three times. Each billet nitrogen present in the sample was determined by back was wrapped with a black polythene bag to prevent titration. )e end of the condenser was then dipped into moisture loss and transported to laboratory for inves- a solution of boric acid. Ammonia was reacted with tigations. In the laboratory, each billet was debarked. )e sulphuric acid and titrated with sodium carbonate so- bark portion and the wood were reduced separately to lution and methyl orange pH indicator at 4.65 for the chip sizes of 10 to 30 mm with the aid of axe. )e wood titration . )e percent of nitrogen was calculated and bark chips were separately put into a container and using carefully labeled. On each chip (wood and bark), the International Journal of Forestry Research 3 (ml standard acid − ml blank) × (N of acid × 1.4007) nitrogen(%) � , (3) weight of sample in g acid − insoluble residue(AIR) � × 1000 mg/g, (4) where ml blank is milliliters of base needed to back-titrate a reagent blank if standard acid is the receiving solution or where m is the weight increase (the residue after drying) in milliliters of standard acid needed to titrate a reagent blank if grams and M is the oven-dry weight of sample (100% dry boric acid is the receiving solution, N is the normality of acid, matter) before acid hydrolysis/suspension, in grams: and 1.4007 is the milliequivalent weight of nitrogen × 100%. A × D × V acid − soluble lignin(ASL) � × 1000 mg/g, a × b × M 2.4. Determination of Chemical Content (5) 2.4.1. Lignin Content. Lignin content was determined using where A is the absorption at 205 nm, D is the dilution factor, TAPPI , where 100 mg of the wood sample was weighed V is the volume of the ﬁltrate, a is the extinction coeﬃcient of and placed into a glass beaker with a volume of at least lignin in grams per centimeter, b is the cuvette path length, 150 ml, and 1.0 ml of 72% sulphuric acid was added to the in centimeter, and M is the weight of sample (as 100% dry beaker with a pipette. )e contents in the beaker were stirred matter) before acid hydrolysis/suspension in grams: with a glass rod until the samples began to dissolve. )e total lignin content � AIR + ASL. (6) beakers were placed in a 30 C water bath for 1 h and stirred occasionally. )en, 28.0 ml of water was added and the beakers were covered with aluminum foil and placed in an autoclave at 120 C for 1 h. )e beakers and their contents 2.4.2. Extractive Content. Extractive content was deter- were allowed to cool to 80 C . mined using dichloromethane solvent extraction method )e contents of the beakers were ﬁltered while still hot (TAPPI ). Five grams of wood sample was subjected to through a single or double preweighed glass ﬁber ﬁlter. )en, 105 C oven-drying for 12 hours and then removed and the ﬁltrate was transferred to a separate beaker (this ﬁltrate is allowed to cool in desiccators and weighed to the nearest used for the determination of acid-soluble lignin). )e 0.1 mg. )en, the sample was poured into a beaker and 50 ml retained residues were washed with hot water until acid-free of dichloromethane was added. )en, the beaker was cov- (checked with pH-indicator paper). )e ﬁlters with residues ered with nylon to prevent the solvent from escaping and from the ﬁlter container were removed carefully and allowed allowed to dissolve overnight. )en, the extract was ﬁltrated to dry overnight at 105 C and cooled in desiccators and the and the solvent was allowed to escape completely. )en, the decrease was weighed (i.e., the acid-insoluble residue). extract was oven-dried and allowed to cooled and weighed. )e content of acid-soluble lignin was determined in the )e percentage extractive was determined using ﬁrst ﬁltrate by spectrophotometer at 205 nm. )e ﬁltrate was diluted until absorption was in the range 0.2–0.7 AU : weight of flask plus extractive − weight of flask extractive(%) � × 100%, (7) ODW sample where ODW is the oven-dried weight. 4. Results and Discussion )e nutrient elements are those elements that make up the 3. Statistical Analysis various components of wood (cellulose, hemicelluloses, lignin, and others) which contributes mainly to the heating A two-factor factorial experiment in a completely ran- value of fuelwood species. domized design was employed for this study: Y � µ + A + B + (AB) + E , (8) ijk i j ij ijk 4.1. Carbon Content. )e results of this study reveal that the average carbon content obtained for all the selected trees in where Y is the individual observation, µ is the general mean, ij this study ranges from 49.54% in A. sieberiana to 50.98% A is the eﬀect of variation in tree species (factor A), B is the i j obtained in A. leiocarpus (Table 1). )is range is similar to eﬀect of variation in bark content (factor B), AB is the eﬀect ij those recorded for some indigenous tree species by Deka of interaction between factors A and B, and E is the ex- ijk et al.  but higher than those reported for some hard and perimental error. softwood species by Telmo and Lousada . Meanwhile, 4 International Journal of Forestry Research Table 1: Eﬀect of bark inclusion on the carbon contents (%) of selected fuelwood species. Carbon Tree species 100% W 5% B 10% B 100% B Mean a a a b a A. leiocarpus 50.99 50.84 50.13 48.71 50.98 a b b c ab C. arereh 53.45 51.31 50.58 48.60 50.16 a ab bc c b B. aegyptiaca 51.24 50.59 49.26 47.94 49.76 a a a a b C. molle 50.52 49.78 49.40 49.34 49.76 a a ab b b T. mollis 50.54 50.38 49.63 48.29 49.72 a a a a b T. indica 50.30 50.11 49.57 48.85 49.71 c ab b c b S. birrea 50.67 50.36 49.83 47.94 49.58 a a a b b C. lamprocarpum 50.49 50.12 49.79 48.19 49.65 a ab b c b P. reticulatum 50.92 50.07 49.41 47.93 49.58 a a a a b A. sieberiana 50.46 50.02 49.27 48.42 49.54 W is the wood, and B is the bark. Values with the same alphabets within the same rows are not signiﬁcantly diﬀerent, and values with the same alphabets in the mean column are not signiﬁcantly diﬀerent using Duncan multiple range test at α � 0.05. the addition of 5% and 10% bark fraction reduces the carbon alternately in A. leiocarpus, C. arereh, and C. mole, it in- content of wood by 1.25% and 2.74%, respectively (Figure 1). creases in fuel stock obtained from T. mollis, T. indica, S. However, the carbon content of 100% bark is about 12% birrea, C. lamprocarpum, P. reticulatum, and A. sieberiana. lower compared with wood without bark. )is is similar to However, despite this trend, the oxygen content is lower in what was reported for some indigenous fuelwood species by the bark than in wood without bark except in fuel stock Deka et al. . obtained from P. reticulatum and A. sieberiana, which had higher oxygen content in the bark (Table 3). )is is similar to what was reported by Telmo and Lousada . However, in a 4.2. Hydrogen Content. )e hydrogen content ranges from study carried out by Demirbas and Arin  on Spruce and 3.99% in P. reticulatum to 4.66% obtained in C. arereh Beech wood, the trunk wood had marginal higher oxygen (Table 2). )e value was similar to those reported for some content than the bark. )e oxygen content has no relation tree species by Telmo and Lousada  but lower than what with heating value of fuelwood species in this study, which was recorded for some indigenous tree species by Deka et al. also corresponds with what was reported by Sheng and . Meanwhile, among the fuel material types, wood Azevedo  and Saidur . contained 1.09% higher hydrogen content than the isolated bark. Similarly, the addition of bark to the tune of 5% and 10% progressively lowered the hydrogen content of the 4.5. Sulphur Content. One of the eﬀects of burning biomass fuelwood species (Figure 1). )e rate, however, varies across for energy of most concern is the atmospheric emission of the tree species. Some authors have also reported lower sulphur dioxide (SO ), diﬀerent nitrogen oxides, and to a hydrogen content in isolated bark compared with wood lesser extent ammonia (NH ), which directly or indirectly without bark [17, 19, 20]. aﬀects natural ecosystems. )e sulphur content in all the selected trees was less than one percent. )e variation in sulphur contents ranges from 0.24% in C. arereh to 0.93% in 4.3. Nitrogen Content. Nitrogen content ranged from 0.31% A. sieberiana (Table 4). )e values obtained in this study in A. leiocarpus to 1.00% in A. sieberiana (Table 2). Among were similar to those recorded for some tree species by the fuel materials used, the isolated bark contained ap- Saarela et al. , but higher than the range of 0.001% to proximately 0.45% nitrogen content compared with wood 0.06% obtained in some tree species by Telmo and Lousada without bark. Similarly, the inclusion of bark fraction to the . Meanwhile, the bark portion contains more sulphur wood fuel in the amount of 5% and 10% alternately increased than its corresponding wood. Similarly, addition of bark the nitrogen content of the fuel materials (Figure 1). )e fraction to the wood fuel stock signiﬁcantly increased the value recorded in this study is similar to those recorded for sulphur content (Table 4 and Figure 1). )e rate of increase, some tree species by Alvarez-Alvarez et al. . however, varies across species. Similarly, increase in sulphur content in the bark compared with wood without bark of some tree has been reported by Garc´ıa et al.  and Wang 4.4. Oxygen Content. )e average oxygen content in the et al. . )e SO emissions are not signiﬁcant for wood selected trees ranges from 40.22% in P. reticulatum to combustion because of the low sulphur content but can be 43.16% in A. leiocarpus (Table 3). )e values recorded were relevant for agricultural residues, grasses, and straw . similar to those reported for some tree species by Telmo and Lousada  and Deka et al. . However, unlike the other mineral elements, the oxygen content did not follow a 4.6. Chemical Compounds of the Ten Selected Fuelwood Species particular order with addition of bark fraction to wood. For example, while oxygen content in the wood fuel decreases 4.6.1. Lignin Content. Lignin is a complex polyphenolic ma- with addition of bark fraction to the tune of 5% and 10% terial arising from enzymatic dehydrogenative polymerization of International Journal of Forestry Research 5 50.94 49.69 50.37 48.42 44.08 42.84 41.61 39.55 5.06 4.68 4.33 3.97 0.86 0.44 0.59 0.87 0.42 0.29 0.63 0.7 CH N OS C H N OS C H N OS C H N OS 100% wood 5% bark 10% bark 100% bark Figure 1: Average elemental composition of the fuelwood materials. Table 2: Eﬀect of bark inclusion on hydrogen and nitrogen contents (%) of selected fuelwood species. Hydrogen Nitrogen Tree species 100% W 5% B 10% B 100% B Mean 100% W 5% B 10% B 100% B Mean a b c d a b ab ab a f A. leiocarpus 5.43 4.79 4.54 4.37 4.78 0.22 0.26 0.29 0.47 0.31 a b c d a c b b a f C. arereh 5.40 4.95 4.66 4.11 4.78 0.22 0.37 0.38 0.55 0.38 a b c d ab c b ab a f B. aegyptiaca 5.41 4.93 4.25 3.73 4.58 0.29 0.39 0.40 0.42 0.38 a ab b b ab c b a a de C. molle 4.98 4.59 4.43 4.33 4.58 0.21 0.49 0.72 0.76 0.55 a ab ab b ab a a a a e T. mollis 4.95 4.67 4.48 4.15 4.56 0.46 0.50 0.49 0.60 0.51 a a a a ab d c b a cd T. indica 4.62 4.79 4.41 4.23 4.51 0.08 0.46 0.76 1.15 0.61 a b c d b c b b a c S. birrea 5.24 4.76 4.40 3.58 4.49 0.19 0.71 0.78 0.96 0.66 a a ab a b c b b a b C. lamprocarpum 4.72 4.67 4.38 4.11 4.47 0.78 0.94 0.96 1.06 0.94 a b c d c b a a a a P. reticulatum 5.17 4.28 3.51 3.02 3.99 1.08 1.22 1.26 1.29 1.21 a b bc c b c b b a b A. sieberiana 1.69 4.37 4.21 4.11 4.34 0.70 0.93 0.95 1.45 1.00 W is the wood, and B is the bark. Values with the same alphabets within the same rows are not signiﬁcantly diﬀerent, and values with the same alphabets in the mean column are not signiﬁcantly diﬀerent using Duncan multiple range test at α � 0.05. Table 3: Eﬀect of bark inclusion on the oxygen content (%) of the Table 4: Eﬀect of bark inclusion on the sulphur content (%) of the selected fuelwood species. selected fuelwood species. Oxygen Sulphur Tree species Tree species 100% 5% 10% 100% 100% 5% 10% 100% Mean Mean wood bark bark bark wood bark bark bark a b c d a b ab ab a d A. leiocarpus 45.26 43.28 42.49 41.61 43.16 A. leiocarpus 0.19 0.22 0.23 0.26 0.33 a b c d a b a a a d C. arereh 45.12 43.80 42.76 40.73 43.10 C. arereh 0.07 0.28 0.29 0.33 0.24 a a b c ab b b b b cd B. aegyptiaca 45.18 43.62 41.48 39.02 42.33 B. aegyptiaca 0.06 0.10 0.11 0.95 0.31 a ab b b ab b b b a c C. molle 43.90 42.65 41.62 40.99 42.29 C. molle 0.37 0.37 0.37 0.41 0.38 a a a b b b b a a b T. mollis 42.17 42.78 43.72 39.81 42.12 T. mollis 0.06 0.15 1.11 1.14 0.62 ab a b c b b b a a b T. indica 42.70 43.12 41.69 40.32 41.96 T. indica 0.11 0.17 1.09 1.14 0.63 b a a a b c c b a b S. birrea 39.49 41.73 42.69 43.08 41.75 S. birrea 0.18 0.22 0.98 1.16 0.64 b a a c b b b a a b C. lamprocarpum 41.85 43.02 44.54 38.11 41.88 C. lamprocarpum 0.22 0.23 0.91 1.25 0.65 d c b a c b b b a a P. reticulatum 35.71 39.16 41.62 44.39 40.22 P. reticulatum 0.81 0.82 0.82 0.995 0.85 b b a c b b b a a a A. sieberiana 41.16 41.83 42.93 39.71 41.41 A. sieberiana 0.85 0.86 0.98 1.01 0.93 Values with the same alphabets within the same rows are not signiﬁcantly Values with the same alphabets within the same rows are not signiﬁ- diﬀerent, and values with the same alphabets in the mean column are not cantly diﬀerent, and values with the same alphabets in the mean column signiﬁcantly diﬀerent using Duncan multiple range test at α � 0.05. are not signiﬁcantly diﬀerent using Duncan multiple range test at α � 0.05. the phenylpropene units. It plays a vital role in the combustion process as a result of reduction state in chemical makeup of the from10.68% in A. sieberiana to 25.39% in A. leiocarpus (Table 5). wood both on the molecular and atomic levels . )e result of )e values obtained are similar to those recorded for some this study shows that the average lignin content obtained for all selected wood species by Miller , Nasser and Aref , and the selected trees in this study was quite high. )e value ranged Deka et al. . Percentage composition 6 International Journal of Forestry Research Table 5: Eﬀect of bark inclusion on the lignin content (%) of selected fuelwood species. Fuel material composition Tree species 100% wood 5% bark 10% bark 100% bark Mean a b c d a Anogeisus leiocarpus 33.00 25.64 23.02 18.88 25.39 a b c d a Caccia arereh 28.07 25.87 24.67 22.24 25.21 a b c d a Balanites aegyptiaca 28.00 25.54 24.33 21.75 24.90 a b c d b Combretum molle 27.04 24.96 23.47 21.24 24.18 a b c d c Terminalia mollis 27.06 25.78 25.08 14.33 23.06 a b c d d Tarmarindus indica 15.12 13.45 11.74 10.15 12.61 a b c d d Sclerocarya birrea 15.00 12.84 11.62 10.11 12.39 a b c d d Combretum lamprocarpum 14.11 12.61 11.62 10.31 12.16 a b c d e Piliostigma reticulatum 12.49 11.50 10.67 9.34 11.00 a b c d e Acacia sieberiana 13.36 10.90 9.89 8.58 10.68 Values with the same alphabets within the same species and among species in mean column are not signiﬁcantly diﬀerent using Duncan multiple range test at α � 0.05. 21.33 18.91 17.61 16.41 14.79 12.62 12.51 11.45 100% wood 5% bark 10% bark 100% bark Lignin Extractive Figure 2: Average lignin and extractive content (%) of the fuel materials from the selected fuelwood species. Meanwhile, lignin content in all the selected species was nature and composition of extractives, and the quantities found to be signiﬁcantly higher in wood than the respective determines the heating value of biofuel for energy purpose. barks. Averagely, lignin content was found to be 6.54% In this study, the average extractive content ranges from higher in wood than the bark. Similarly, the inclusion of 5% 7.31% in A. leiocarpus to 19.33% in P. reticulatum (Table 6). and 10% bark fractions in the wood fuel material lowers the )e values obtained in this study are similar to those recorded for some Acacia species by Nasser and Aref . lignin content by 2.42% and 4.24%, respectively (Figure 2). However, the degree of variation was not constant across Meanwhile, among the fuel material types, isolated bark species (Table 5). Similarly, Deka et al.  reported higher contained approximately 5.0% extractive content more than lignin content in some indigenous fuelwood species wood without bark (Figure 2). Similarly, the addition of bark compared with bark. In general, lignin content plays a vital fraction at 5% and 10%, respectively, increases the extractive role in the combustion process as a result of reduction state content of the fuel material type by 1.06% and 1.17% in chemical makeup of the wood both in molecular and (Figure 2). However, the trend of increment in extractive atomic levels. )e lignin content of wood signiﬁcantly content with bark inclusion onto the wood fuel diﬀers inﬂuences the heating value of wood. )e higher the lignin among tree species (Table 6). Demirbas and Sims  and Deka et al.  reported a similar trend of increment in content, the higher the heating value of the fuelwood species. extractive content for some wood species. Many studies have shown the inﬂuence of extractive content on combustion properties of fuelwood [31, 32] and concluded that extractive 4.6.2. Extractive Content. Extractives are nonstructural and content signiﬁcantly inﬂuences the heating values of biofuel. low molecular weight compound present in wood. )ey However, more extractives are usually found in the bark of include fats, waxes, alkaloid, protein, gum, resins, starch, wood, and therefore it increases the heating value of glycoside, and essential oils, most of which are readily fuelwood. soluble in neutral organic solvents or cold water. )e diverse Percentage composition International Journal of Forestry Research 7 Table 6: Eﬀect of bark inclusion on the extractive content (%) of selected fuelwood species. Fuel material composition Tree species 100% wood 5% bark 10% bark 100% bark Mean b b b a g Anogeisus leiocarpus 6.14 6.18 6.68 10.23 7.31 b a a a e Caccia arereh 8.58 11.01 11.45 11.66 10.68 c b b a f Balanites aegyptiaca 6.05 8.98 9.07 13.28 9.34 b b b a e Combretum molle 8.75 9.57 9.61 16.37 11.07 d c b a d Terminalia mollis 11.53 11.93 12.50 15.13 12.78 c b ab a c Tarmarindus indica 13.83 14.83 14.90 15.40 14.74 c b b a c Sclerocarya birrea 9.99 10.90 11.29 29.96 15.54 b b a a c Combretum lamprocarpum 14.73 14.77 15.40 15.47 15.09 a a a a a Piliostigma reticulatum 19.03 19.13 19.53 19.63 19.33 b a a a b Acacia sieberiana 15.83 16.77 16.80 16.93 16.58 Values with the same alphabets within the same species and among species in mean column are not signiﬁcantly diﬀerent using Duncan multiple range test at α � 0.05. 5. Conclusion References  A. A. 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International Journal of Forestry Research – Hindawi Publishing Corporation
Published: Jul 27, 2020
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