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Chemical elemental characteristics of biomass fuels in China
Biomass and Bioenergy 27 (2004) 119 – 130
Chemical elemental characteristics of biomass fuels in China Liao Cuipinga; b;∗ , Wu Chuangzhia , Yanyongjieb , Huang Haitaoa a Laboratory
of Biomass Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Science, 81 Xianlie Zhong Road, Guangzhou 510070, China b College of Resource and Environment Engineering, East China University of Science and Technology, Rd. Meilong 130, Shanghai 200237, China Received 2 October 2002; received in revised form 10 November 2003; accepted 12 January 2004
Abstract This paper investigates the chemical elemental characteristics of 63 samples of biomass including agricultural biomass such as rice straw, wheat straw, corn straw, cotton straw and forestry biomass such as birch, spruce, willow, etc. in China. Twenty one di1erent biomass groups are distinguished as reference fuels in China. The elemental characteristics of bituminous coal are also presented for comparison. ? 2004 Elsevier Ltd. All rights reserved. Keywords: Biomass; Chemical elemental characteristics; Agricultural biomass; Forestry biomass
1. Introduction Biomass fuels are the 5rst energy source harnessed by mankind. They remain the primary source of energy for more than half the world’s population and account for 14% of the total energy consumption in the world [1]. Biomass is the most common form of renewable energy. The use of renewable energy sources is becoming increasingly important when it is considered to assist to alleviate global warming and provide fuel supply. In the past 10 years, there has been renewed interest, worldwide, in biomass as an attractive alternative to fossil fuels. Especially in developing countries, as it is readily available and when properly managed the resource is renewable and provides an indigenous fuel supply at lower cost. ∗ Corresponding author. Laboratory of Biomass Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Science, 81 Xianlie Zhong Road, Guangzhou 510070, China.
0961-9534/$ - see front matter ? 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.biombioe.2004.01.002
Using biomass as a source of fuel has little adverse environmental impact. The combustion of biomass produces signi5cantly less nitrogen oxide and sulphur dioxide than the burning of fossil fuels. Liquid biomass fuels like ethanol and methanol produce less carbon monoxide, hydrocarbons and potentially carcinogenic compounds than gasoline and diesel. Unlike fossil fuel combustions, the use of biomass fuels will not contribute to carbon dioxide levels that cause global warming. Biomass fuels are always the main kinds of energy resources except for coal in China. But they are used normally as a primary source of energy for domestic purposes in a low-eFciency way of combustion. In China, a total of 939 million tons of agricultural biomass residues produced each year and 551 million tons can be used as an energy resource, but only 266 million tons residues are used. With regard to forestry residues, there is a total 227 million tons yields in China of which 123 million tons are
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L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
used [2]. With the implementation of R& D policy of sustainable energy of government, people realize the environmental bene5ts of biomass fuel. It is time to explore and utilize the biomass fuels in a clean and more eFcient way; however, there is a conspicuous lack of knowledge with regard to the chemical elemental characteristics of biomass fuels in China which is very important for utilization of them as energy sources. Modeling and analysis of energy conversion processes require adequate fuel characteristics especially average and variations in elemental compositions [3]. Knowledge of the concentration and speciation of alkali elements in fuels is useful for studies of BIGCC or other biomass power generation topics. The concentration and speciation of heavy metal elements is related to environment-related topics. With regard to the utilization of biomass as an energy source, the investigation of chemical elemental characteristics of biomass fuels is bene5cial for biomass fuels to 5nd suitable energy conversion technologies and for various energy conversion processes to utilize favorable biomass feedstock. Researchers in several countries have carried out extensive research to determine
the properties of their own available biomass resources [5–9]. In this paper, chemical elemental characteristics of biomass fuels are presented. The categories of biomass analyzed in this study are agricultural biomass and forestry biomass. 2. Sample collection 2.1. Sampling region Sample collection was based on the investigation of the distribution and quantity of biomass residues resource in China [2]. The samples were collected from the main production regions of straw and stalk such as East China, South China, North China and Northwest China, also from the regions with the highest forestry residues availability such as Northeast China and North China represented by Northeast China National Forest Region, Southwest China represented by Southwest China National Forest Region and South China represented by Southern Collective Forest Region. The sampling region can be seen in Fig. 1.
Fig. 1. Map of China with indications of sampling region on it.
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
2.2. Sampling type The agricultural biomass samples collected include traditional biomass fuels such as rice straw, wheat straw, corn cob, corn stalk, cotton stalk, peanut stalk, rape stalk, soybean stalk, sesame stalk, broad bean stalk, peanut hull, cotton shuck, etc. Forestry biomass samples collected include wood species such as birch (Betula), spruce (Picea asperata), willow (Salix), pine tree (Pinus tabulaeformis), poplar (Populus tomentosa), metasequois (Metasequoia glyptostroboides), phoenix tree (Paulownia catalpifolia) and fast-growing energy trees such as foliole eucalyptus (Eucalyptus) and rubber plants. The majority of these biomass species selected for the present study are among the highest yields. Although the wood fuels as pine, spruce, poplar, willow and birch are quite similar in composition, they were put in a separate group. The cluster analysis showed that the varieties are clustered to the same species group more than site, i.e. the e1ects of species are more important than that of growing regions. Chemical elemental characteristics of 21 di1erent groups are presented. Among them, there are eight groups that contain samples from only one region, in this situation; the data relating to these groups are presented with average values and without standard deviations. 2.3. Sample preparation and analysis Five kilogram of each sample was collected from the region and air dried, then ground twice and sieved to 200 mesh, and the 5nal analysis sample taken according to quartation. (LY/T 1211-1999)[10](LY/T 1211-1999 is professional standard that covers 5eld sampling and preparation of forest plant and forest Noor samples issued by Chinese National Bureau of Forest. This standard is issued under the 5xed designation LY/T 1211; the number immediately following the designation indicates the year of original adoption.) The analysis program includes proximate analysis of moisture, ash, volatile matter and the calculation of 5xed carbon according to GB212-91 [11] (GB212-91 is standard which covers the determination of moisture, volatile matter, and ash and the calculation of 5xed carbon on coals. This standard is issued under
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the 5xed designation GB212; the number immediately following the designation indicates the year of last revision.); and the determining of calori5c value by WGR-1 calorimeter according to Chinese national standard (GB 5186-85 [12]: Testing methods for heat value of biomass fuels.); and ultimate analysis of C, H, O, N and S content for all samples by Elementary Vario EL. The chemical compositions of alkali metals and other ash-forming elements such as Al, Si, Ca, Fe, K, Mg, Na, P and trace elements such as As, Ba, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, Ti, V, Zn for all samples collected were analyzed. Samples were digested with 5:1 mixture of HNO3 : HClO4 and made up to 25 ml with high-puri5ed water derived from vaporizing of deionized water under boiling point and analyzed using ICP-Model IRIS 1000 ER/S (TJA Corp.). All analyses are performed on three repeats and averages presented. When the content is 10 ppm, the RSD is no more than 2%. The detective limits were carefully determined as triple standard deviation of blank. Three kinds of bituminous coal were also investigated for comparison. 3. Results and discussion 3.1. Proximate and ultimate analysis results The main material properties of interest of biomass as an energy source are also taken into investigation. Tables 1 and 2 list these characteristics of the reference fuels. Table 1 lists the moisture content, ash content, proportions of volatile matters and 5xed carbon together with calori5c value. Table 2 lists the elemental analysis of N, C, S, H and O. The reference biomass fuels are presented with their average characteristics compositions and standard deviations. Moisture content is of considerable importance with regard to selection of energy conversion process technology. Biomass fuels with low moisture content are more suited for thermal conversion technology while biomass fuels with high moisture content are more suited for biochemical process such as fermentation conversion [1]. On this basis, from Table 1, it can be seen that biomass fuels under this investigation are most favorable biomass feedstock for thermal conversion technologies with their moisture content in the range 6–10%.
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Table 1 Characteristics of the reference fuels—proximate analysis Group
Moisture (wt%)
Ash (wt% db)
Volatile matter (%)
Fixed carbon (%)
C.V (MJ/kg)
Rice straw Wheat straw Corn straw Soybean Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean stalk Rape stalk Foliole eucalyptus Rubber plant Willow tree Poplar Pine tree Spruce Phoenix tree Birch tree Metasequoia Bituminous coal
8:11 ± 1:51 8:63 ± 2:03 9:31 ± 2:05 9:34 ± 1:88 6:41 ± 2:81 7:66 ± 1:86 10.23 9:36 ± 0:41 8.56 7.66 7.62 6.15 6:5 ± 1:2 8:88 ± 2:27 9:08 ± 1:45 7:91 ± 1:65 8:61 ± 1:91 9:21 ± 0:5 7.74 9.06 7.38 2:83 ± 0:66
15:25 ± 2:64 12:45 ± 9:02 13:12 ± 8:79 6:08 ± 1:10 7:55 ± 6:91 6:41 ± 3:08 6.88 12:15 ± 3:02 9.12 6.11 5.03 3.60 5:55 ± 2:44 9:9 ± 3:31 6:17 ± 3:7 2:63 ± 0:87 0:89 ± 0:13 5:36 ± 2:33 5.28 2.36 2.20 20:08 ± 3:49
61:10 ± 2:51 63:96 ± 7:29 62:74 ± 6:15 68:95 ± 1:74 70:24 ± 6:43 67:36 ± 3:49 62.16 61:64 ± 1:9 66.67 68.93 68.44 72.99 67:75 ± 5:01 62:92 ± 5:59 69:2 ± 5:08 74:04 ± 0:36 76:50 ± 2:45 71:04 ± 3:26 68.68 74.91 74.30 28:33 ± 1:89
15:54 ± 1:36 14:96 ± 1:49 14:83 ± 2:13 15:62 ± 0:17 15:8 ± 1:85 18:57 ± 1:14 20.74 16:85 ± 0:71 15.66 17.30 18.90 17.26 20:19 ± 2:77 18:3 ± 1:44 15:55 ± 1:99 15:42 ± 1:14 14:45 ± 0:41 14:39 ± 5:09 18.29 13.68 16.11 49:08 ± 2:12
14:66 ± 0:71 16:56 ± 1:05 16:64 ± 0:38 16:96 ± 0:62 16:98 ± 0:64 17:91 ± 0:47 17.88 18:62 ± 0:21 15.75 15.92 16.31 16.65 19:33 ± 1:60 18:14 ± 1:30 18:79 ± 0:40 18:57 ± 0:17 19:38 ± 0:35 18:93 ± 0:71 17.96 19.34 19.62 34
Table 2 Characteristics of the reference fuels—ultimate analysis Group
N
C
S
H
O
Rice straw Wheat straw Corn straw Soybean Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean Rape stalk Foliole eucalyptus Rubber plant Willow tree Poplar Pine tree Spruce Phoenix tree Birch tree Metasequoia Bituminous coal
0:69 ± 0:21 0:58 ± 0:28 0:99 ± 0:20 0:95 ± 0:28 0:49 ± 0:12 1:09 ± 0:10 1.23 1:17 ± 0:09 2.06 0.81 0.97 0.23 0:50 ± 0:47 0:97 ± 1:04 0:77 ± 0:79 0:17 ± 0:06 0:10 ± 0:02 0:20 ± 0:10 0.70 0.16 0.11 1:13 ± 0:01
38:52 ± 1:03 42:11 ± 2:12 42:69 ± 1:47 43:16 ± 1:13 44:53 ± 0:50 46:10 ± 0:49 44.54 45:90 ± 0:54 40.28 41.34 42.16 42.42 50:15 ± 2:55 48:69 ± 1:69 46:79 ± 1:14 47:46 ± 0:45 49:41 ± 0:24 48:56 ± 0:25 48.14 48.32 47.98 63:78 ± 2:33
0:29 ± 0:17 0:32 ± 0:10 0:21 ± 0:13 0:20 ± 0:04 0:11 ± 0:05 0:26 ± 0:09 0.39 0:18 ± 0:05 0.28 0.29 0.24 0.27 0:02 ± 0:03 0:11 ± 0:09 0:30 ± 0:17 0:10 ± 0:09 0:05 ± 0:04 0:18 ± 0:17 0.04 0.20 0.08 0:97 ± 0:19
6:13 ± 0:49 6:53 ± 0:46 6:16 ± 0:81 6:9 ± 0:13 6:89 ± 0:10 6:85 ± 0:39 6.66 6:74 ± 0:27 7.18 6.57 6.13 7.06 7:45 ± 0:46 7:29 ± 0:60 7:10 ± 0:44 6:74 ± 0:02 7:67 ± 0:42 6:53 ± 0:52 7.88 8.36 6.82 3:97 ± 0:38
39:28 ± 2:14 40:51 ± 2:67 42:69 ± 2:11 44:76 ± 2:42 45:97 ± 1:51 43:35 ± 2:63 46.66 42:79 ± 0:05 42.47 45.16 45.28 46.10 39:64 ± 3:88 39:03 ± 3:25 40:60 ± 3:75 44:50 ± 1:36 42:19 ± 0:61 43:55 ± 1:55 39.84 40.60 43.98 10:08 ± 4:66
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The ash content of biomass a1ects both the handling and processing costs of the overall biomass energy conversion cost. The chemical compositions of the ash are closely related to operational problems such as slagging, fouling, sintering and corrosion. From Table 1, it can be seen that ash content ranged from 0.89–15.24% depending on biomass type. Forestry species have much lower ash content comparing with agricultural species. Volatile matter is in the range of 61–76%, forestry biomass has a somewhat higher volatile matter than agricultural biomass. While the ash content and volatile matter in bituminous coal is 20% and 28%, respectively. So, Biomass fuels have the advantages of low ash content and high volatile matter that make them the ideal feedstock for pyrolysis and gasi5cation. The elemental contents of N, C, S, H and O listed in Table 2 show clearly that these biomass fuels contain higher proportion of hydrogen and oxygen, compared with carbon, which reduces the energy value. It is said that carbon–oxygen and carbon– hydrogen bonds contain lower energy than in carbon–carbon bonds. So, the calori5c value of biomass is in the range of 16–20 MJ=kg. Forestry biomass fuels contain a slightly higher calori5c value than agricultural biomass. The calori5c value of bituminous coal achieves 34 MJ=kg, which is much higher than that of biomass. The lower content of nitrogen and sulphur in biomass fuels compared with coal is especially important for environment protection. 3.2. The chemical elemental characteristics of the reference fuels Table 3 shows some of the most important trace elements in the reference fuels. Table 4 shows the major elements (ash-forming elements) characteristics of the reference fuels. The data are presented as average values and standard deviations. 3.2.1. Ash-forming elements The ash-forming elements such as Al, Si (in this investigation only soluble Si is determined), Ca, Fe, K, Mg, Na and P in biomass are especially important for any thermochemical conversion process. The relatively high contents of alkali may lead to a serious technical problem when used as feedstock for
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power production. It is generally believed that alkali metals are the main cause of slagging, fouling and sintering. In Tables 3 and 4, the 5rst 12 groups of the tables represent the agricultural biomass residues; the next nine groups represent forestry biomass. The tables show some clear di1erences among the fuel data for agricultural biomass residues and forestry biomass. From Table 4, it can be seen that the concentrations of Al, Si, Ca, Fe, K, Mg, Na and P in agricultural biomass fuels are generally higher than in forestry biomass, accounting for most of the top 10 high-concentration species of each element. Except Al, Si, Ca, Fe, Mg, P in rubber plant, Ca in willow, poplar and phoenix tree, Fe in foliole eucalyptus and willow, Na in foliole eucalyptus and spruce also belong to top 10 concentrations. In the same group, the content ranges from high to low as Ca, K ¿ Fe, Mg, P, Al ¿ Na, Si for almost all the agricultural biomass groups. Na in broad bean stalk and rape stalk is much higher than other elements but Ca. Al is much lower in these two groups than other elements but Si. The agricultural biomass residues contain much higher K than forestry biomass. K accounts for the 5rst high content in rice straw, wheat straw, corn stalk, corn cob, rape stalk and cotton stalk and cotton shuck. For forestry biomass, the sequence is Ca¿K¿Fe, Mg¿Al, P¿Na, Si, the exceptional case is that Na in foliole eucalyptus is larger than Mg, P and Al. Al in spruce tree ¿Mg. P in foliole eucalyptus ¿Al. The extreme properties of straw with respect to high potassium content are a major obstacle for an eFcient utilization of straw as a fuel for power production. 3.2.2. Trace elements It is seen that the content of most of the trace elements is higher in agricultural biomass than in forestry biomass. Foliole eucalyptus and rubber plant have relatively high content of these gaseous pollutant-forming elements because the samples of the two groups are the mixture of leaves, branches, trunks, roots and bark. According to our experiments, these elements in roots and leaves are much higher than in other parts of the trees. Some wood species also contain high amount of Cr, Cu, Mn, Zn. The amount of elements in the same group ranks from high to low approximately as Ti, Mn¿Ba,
As 5:327 ± 4:900 0:711 ± 0:567 1:627 ± 1:141 0:58 ± 0:31 1:080 ± 0:308 0:472 ± 0:147 0.750 1:123 ± 0:123 1.2509 1.2501 0.250 ND 1:001 ± 0:492 1:532 ± 1:889 0:594 ± 0:361 0:246 ± 0:002 0:249 ± 0:000 1.993 0.4250 0.25 0.24 14.5
Ba 72:1946 ± 36:9716 63:4064 ± 34:5446 24:7526 ± 21:1150 56:0804 ± 17:7757 24:5802 ± 16:1562 21:9475 ± 11:4834 19.887 49:7896 ± 22:0091 47.4082 72.3822 35.404 15.1159 0:6128 ± 0:3930 1:0623 ± 1:0052 23:3135 ± 16:8346 40:6391 ± 5:6746 52:1017 ± 16:5829 17:1434 ± 3:1438 ND 125.04 30.29 na
Cd 0:9206 ± 1:0268 0:4602 ± 0:4464 0:5540 ± 0:3904 0.28 0:3462 ± 0:2607 0:2766 ± 0:2285 0.300 0:3302 ± 0:2802 0.2752 0.3250 0.050 0.5497 0:1101 ± 0:0684 0:5916 ± 0:3440 0:8661 ± 0:9164 0.2916 0.14 0:1746 ± 0:0496 0.5301 ND ND 0.19
Group
Mo
Ni
Pb
Rice straw Wheat straw Corn stalk Soybean stalk Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean stalk Rape stalk Foliole eucalyptus Rubber plant Willow Poplar Pine tree Spruce tree Phoenix tree Birch tree Metasequoia
2:147 ± 1:360 3:443 ± 6:604 6:691 ± 11:420 2:508 ± 0:357 1:199 ± 0:436 2:001 ± 1:752 0:9005 1:634 ± 0:334 13.4594 2.9253 2.7753 4.1225 1:751 ± 1:886 5:690 ± 6:537 1:535 ± 1:466 ND 0.12 ND 1.5002 0.0996 ND
6:737 ± 9:841 10:105 ± 16:138 16:703 ± 29:044 2:478 ± 1:314 4:525 ± 3:043 5:611 ± 6:170 2.5515 3:069 ± 0:344 4.5282 2.3002 1.1501 0.5747 45:181 ± 50:122 60:312 ± 38:112 10:594 ± 14:781 1:821 ± 0:754 2:303 ± 0:933 0:887 ± 0:264 11.2511 2.3902 3.2926
25:01 ± 23:68 13:73 ± 7:77 14:36 ± 8:06 12:32 ± 7:39 63:18 ± 38:12 36:08 ± 55:63 25.0150 20:14 ± 8:39 23.7666 17.5018 13.0013 7.4955 8:46 ± 6:90 5:65 ± 3:14 10:97 ± 5:89 7:148 ± v3:203 5:166 ± 2:077 7:409 ± 2:156 0.7501 14.7147 9.9483
Bituminous coal*
na
13.9
20.9
Co 0:750 ± 0:242 1:088 ± 1:147 1:501 ± 1:709 0:557 ± 0:307 9:071 ± 11:278 0:521 ± 0:273 0.500 1:2097 ± 0:4096 1.2759 0.3750 0.225 ND 0:8054 ± 0:5305 1:7053 ± 1:0413 1:0343 ± 0:6555 0:6849 ± 0:2384 0:3361 ± 0:0621 0:3246 ± 0:0256 0.9251 0.92 0.56 8.5 Ti 38:61 ± 20:93 133:80 ± 195:42 213:69 ± 255:64 80:68 ± 73:56 92:47 ± 92:24 42:79 ± 26:30 61.7871 156:80 ± 68:53 126.3384 38.2538 15.2515 12.2427 60:06 ± 66:20 155:74 ± 119:93 47:45 ± 33:48 15:63 ± 7:50 10:02 ± 0:39 12:23 ± 6:73 45.0295 23.8024 29.2568 na
Cr 7:20 ± 4:30 11:70 ± 8:45 23:18 ± 21:57 3:41 ± 1:53 4:98 ± 2:34 4:94 ± 1:39 8.005 7:74 ± 0:48 5.2537 4.0004 3.500 2.2487 8:76 ± 8:92 12:79 ± 10:42 10:18 ± 8:09 7:68 ± 4:95 7:59 ± 3:61 3:00 ± 0:01 5.8006 9.71 12.23 36.8 V 1:786 ± 0:909 5:559 ± 6:738 9:356 ± 10:540 4:147 ± 4:200 5:406 ± 2:908 1:968 ± 0:836 2.8017 6:060 ± 2:984 3.0021 1.4251 1.6252 1.2742 1:996 ± 1:370 5:041 ± 4:722 1:794 ± 1:324 0:392 ± 0:119 0:386 ± 0:012 0:999 ± 0:127 1.8752 0.5478 0.9643 76.5
Cu 15:792 ± 9:510 65:886 ± 144:206 10:0482 ± 1:7546 9:3702 ± 0:9681 33:3247 ± 46:0969 13.508 14:0014 ± 0:2487 13.0091 23.0023 13.001 10.7436 35:020 ± 54:982 18:012 ± 9:120 76:481 ± 62:887 6:985 ± 1:131 6:423 ± 2:861 17:728 ± 3:969 8.2258 128.473 7.079 27.5 Zn 96:998 ± 96:417 29:357 ± 12:684 69:695 ± 67:355 11:963 ± 3:851 29:944 ± 12:091 24:592 ± 7:794 26.0156 29:494 ± 12:238 0.0000 13.2513 11.0011 12.9922 26:668 ± 15:341 89:231 ± 49:449 162:891 ± 130:758 68:613 ± 17:490 28:604 ± 17:667 14:920 ± 8:094 84.1084 108.6047 26.9991 na
Mn 1051:4858 ± 394:1487 94:5163 ± 55:1850 103:0021 ± 83:4222 68:3292 ± 26:9314 58:5857 ± 43:1590 48:1983 ± 30:3302 85.30 81:5926 ± 25:8314 87.8115 47.2547 28.75 24.7352 783:0643 ± 726:7773 507:0914 ± 397:1799 77:9378 ± 67:7102 29:8545 ± 2:5924 102:0932 ± 19:9297 124:0600 ± 69:5562 51.7552 81.217 17.121 na
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Rice straw Wheat straw Corn stalk Soybean stalk Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean stalk Rape stalk Foliole eucalyptus Rubber plant Willow Poplar Pine tree Spruce tree Phoenix tree Birch tree Metasequoia Bituminous coal*
Group
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Table 3 Characteristics of the reference fuels—trace elements (ppm)(dry biomass basis)
Group
Al
Si
Ca
Fe
K
Mg
Na
P
Rice straw Wheat straw Corn stalk Soybean stalk Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broadbean stalk Rape stalk Foliole eucalyptus Rubber plant Willow Poplar Pine tree Spruce tree Phoenix tree Birch tree Metasequoia
967:36 ± 724:22 2052:36 ± 2459:83 4111:26 ± 4307:71 1336:36 ± 1012:86 2214:28 ± 2229:63 1243:65 ± 893:20 1796.0776 3037:49 ± 674:52 5001.0007 977.5978 450.0450 309.8141 707:42 ± 696:86 1900:12 ± 2398:09 753:06 ± 422:20 215:64 ± 62:09 120:65 ± 6:05 398:13 ± 10:40 595.0595 273.3791 457.4318
351:12 ± 217:73 170:10 ± 97:55 61:12 ± 71:72 14:66 ± 12:57 20:71 ± 14:55 12:31 ± 6:29 60.7865 62:10 ± 37:17 65.7961 12.2512 14.2514 6.4961 17:71 ± 9:74 67:14 ± 60:54 16:47 ± 19:35 1:6280 1:61 ± 1:61 3:99 ± 2:02 13.2513 5.7514 5.0329
4537:838 ± 1505:049 6527:8652 ± 3877:5945 9226:1746 ± 4213:4972 16159:4205 ± 1181:2845 9807:7677 ± 6793:7258 10347:4381 ± 6313:1003 9730.8385 10909:4207 ± 2745:2878 23301.3109 19351.9352 12823.7824 10773.5359 8787:7834 ± 5911:8360 11832:8977 ± 3680:1709 14591:4575 ± 7421:0828 13790:5867 ± 1905:7881 1757:2681 ± 187:4254 9331:7267 ± 7988:4207 12703.7704 7275.1718 5416.2747
1606:295 ± 896:084 2918:810 ± 3096:329 4867:475 ± 5159:783 1500:298 ± 899:227 3152:405 ± 3393:380 2383:605 ± 2213:734 1328.2970 4473:248 ± 2362:826 3982.7880 955.0955 670.0670 382.2706 1942:497 ± 1294:743 4017:759 ± 3242:818 1796:940 ± 1362:303 826:954 ± 497:276 673:203 ± 305:739 492:547 ± 42:277 2550.2550 935.6638 941.9097
21969:67 ± 8063:72 15659:31 ± 3718:68 14302:99 ± 7683:98 9986:00 ± 2773:25 14380:13 ± 4441:44 9086:181 ± 2716:262 9805.8835 9671:27 ± 819:506 6854.7984 12326.2326 5200.5201 10893.4639 4446:66 ± 4031:99 7421:92 ± 6365:41 7239:40 ± 5117:17 3250:32 ± 596:02 826:00 ± 19:79 1055:07 ± 579:79 6558.1558 2063.5395 1174.7413
2587:8107 ± 957:9750 2491:4973 ± 1308:8870 4767:2333 ± 2345:8982 7613:4081 ± 996:0624 2310:1995 ± 1316:9051 2507:6860 ± 1341:4089 4275.0650 3170:6482 ± 740:6622 10855.0986 3465.3465 2088.4588 1266.7400 938:6259 ± 926:0545 3292:4705 ± 2097:2242 2075:1650 ± 1619:3907 1145:9592 ± 60:4263 260:4646 ± 14:5752 305:4253 ± 55:5253 2161.2161 757.1457 507.5259
869:370 ± 609:402 319:167 ± 271:102 571:285 ± 674:656 161:251 ± 73:167 268:885 ± 81:924 718:527 ± 425:150 150.0901 176:120 ± 1:085 300.2101 275.0275 10051.0051 3497.9013 1090:447 ± 1181:92 242:047 ± 58:532 230:492 ± 182:779 70:035 ± 38:357 30:720 ± 14:721 248:565 ± 148:505 140.0140 44.0942 24.0593
1458:212 ± 536:016 1122:847 ± 1047:706 1849:333 ± 941:679 1559:032 ± 579:332 1299:590 ± 584:728 1815:397 ± 829:100 1665.9996 1391:651 ± 163:905 1828.7801 1605.1605 977.5978 342.2946 850:867 ± 588:926 1386:220 ± 1480:239 1005:410 ± 793:537 347:374 ± 119:485 91:882 ± 43:096 94:433 ± 11:884 1102.6103 210.7609 103.0574
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Table 4 Characteristics of the reference fuels—major elements (ash-forming elements)(dry biomass basis)
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L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Zn¿Pb, Cu¿Cr, Ni¿V, Mo, As¿Co, Cd in agricultural biomass and Mn, Ba, Ti, Zn¿ Pb, Cu, Cr, Ni¿ V, Mo, As, Co, Cd in forestry biomass. The content of Cl in biomass has not been studied in this investigation because of the limitation of analysis method. According to Nordin [3], the Cl content has a large variation of 0.008–0.74% dry basis. Faaij [4] found that Cl content is in a range of 0–1.1% dry basis, and the chlorine concentration vary widely between samples and a higher chlorine concentration can also be found close to the sea. 3.3. Composition range 3.3.1. Composition range of the biomass fuels in China Figs. 2 and 3 show the ranges of variation of various compositions that has been observed for the analyzed samples. The range found in composition data should be considered as indications of the possible variations caused by characterization procedures and the origin of the biomass samples [4]. Very wide ranges of the composition content of the biomass materials are found within the same biomass group and between groups. Tick marks in the 5gures present average values. Fig. 2 shows the composition content range of ash-forming elements for the reference fuels. A high K and Si contents is found in rice straw. Poplar, pine tree and spruce tree have the lowest K and Si content. A high K and Si contents have great a1ection on the power production from biomass. So rice straws are considered to be the unfavorable feedstock for power production. Ca content is especially high in willow tree and vary widely between samples. Na is extremely high in foliole eucalyptus and also varies widely between samples. Al, Mg, Fe are found to be high in corn stalk. Soybean stalk has the highest Mg content. Fig. 3 shows the content range of trace elements for the reference fuels. N and S as the most important elements with regard to the system emissions are also presented in Fig. 3. But comparing to coal, N and S content is much lower in biomass fuels than in coal (see Table 2). From Fig. 3, it can be seen that As, Cd, Mn, Zn in rice straw, Co, Pb in corn cob; Cr, Cu, Mo, Ti, V in corn stalk are high. Generally speaking, agricultural biomass fuels con-
tain higher heavy metal concentrations than forestry biomass fuels. Levels are high for Cd, S, N and Zn in willow wood. Foliole eucalyptus and rubber plants show high concentration of Ni, Mn and Cr. These trace elements, most of them, as heavy metals, have much inNuence on gas emission and ash composition characteristics. 3.3.2. Comparison with other studies on biomass compositional analysis A comparison with the studies of Nordin [3] and Sander [4] on biomass compositional analysis is showed in Table 5. Nordin presented compositions of a set of chemically well-characterized biomass reference fuels that were extracted from literature and some other sources of existing property data on biomass-related fuels. Bo. Sander gave the composition of straw and wood chips, which are the most abundant biofuels in Denmark. From the table, it can be seen that Si, Mg and Na are outlier in this paper compared to other studies; Si content is very small in this investigation because only soluble Si is determined. The groups investigated in this paper with the highest Mg and Na contents, which are an order of magnitude higher than in other groups, were sampled from Shanxi province; these two species were not included in studies of Nordin and Sander. They could be caused by the di1erence between species and the inNuences of growing conditions; but this remains to farther research. Comparing with the second highest contents of Mg and Na that are presented in parentheses, the ranges of most elements are comparable in this paper with Nordin. No signi5cant di1erences are observed. But the ranges of elemental compositions presented in Sander’s paper were much lower, because only two species in Denmark were investigated. This might also prove the di1erences between species.
4. Conclusions • Based on the experimental ber of biomass samples, are distinguished as the agricultural biomass and China.
data of a large num21 di1erent groups reference fuels of forestry biomass in
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Fig. 2. Composition content range of ash-forming elements for reference biomass fuels.
127
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L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Fig. 2. continued.
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
129
Fig. 3. Composition content range of trace elements and N, S for reference biomass fuels.
• Biomass fuels have signi5cantly di1erent elemental characteristics compared with those of coal. It is clear that biomass fuels can reduce the environmental impact of burning fossil fuels to produce energy determined by their intrinsic properties. • Biomass fuels are composed of very heterogeneous constituents. Very wide ranges are found within the
same biomass group and between biomass groups for elemental composition content. Comparison shows that the ranges of elemental compositions presented in this paper are consistent with other studied in most elements. • Agricultural biomass contains much more ashforming elements and trace elements than most of forestry biomass.
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Table 5 Comparisons on biomass compositions Element
China
Nordin
Sander
Element
China
Nordin
Sander
N (wt%) C (wt%) S (wt%) H (wt%) O (wt%) Al (ppm) Si (ppm) Ca (ppm) Fe (ppm) K (ppm)
0.11–2.06 38.52–50.15 0.02–0.39 6.13–8.36 39.03–46.66 120–5001 1.6–351 (soluble) 1757–23301 382–4867 826–21969
0.12–3.1 44.0–58.8 0.009–0.26 5.7–6.3 32–46.2 19–2200 28–46000 650–16000 26–1600 400–25000
0.1–1.5 47–52 0.1–0.2 5.2–6.4
Mg (ppm) Na (ppm) P (ppm) Cu (ppm) Zn (ppm) Pb (ppm) Cd (ppm)
260–7613(10855) 24–3497(10051) 91–1849 6.4–128 11–162 0.75–63 0.05–0.92
160–1800 110–2000 75–2900 1.8–62 22–120 1.5–86 0.01–0.02
400–700 150–500 200–800
50–150 1000–8000 2000–4000 150–1000 1000–10000
References [1] McKendry P. Energy production from biomass (part 1): overview of biomass. Bioresource Technology 2002;83: 37–46. [2] Liao CP, Yan YJ, Wu CZ, Huang HT. Study on the distribution of biomass residues resource in China. Research report, 2001. [3] Nordin A. Chemical elemental characteristics of biomass fuels. Biomass and Bioenergy 1994;6(5):339–47. [4] Faaij A, Doorn JV, Curvers T, Waldheim L, Olsson E, Ad van Wijk, Daey-Ouwens C. Characteristics and availability of biomass waste and residues in the Netherlands for gasi5cation. Biomass and Bioenergy 1997;12(4):225–40. [5] Bo Sander. Properties of Danish biofuels and the requirements for power production. Biomass and Bioenergy 1997:12(3):177–83. [6] Kataki R, Konwer D. Fuelwood characteristics of some indigenous woody species of north-east India. Biomass and Bioenergy 2001;20:17–23.
[7] van der Drift A, van Doorn J, Vermeulen JW. Ten residual biomass fuels for circulating Nuidized-bed gasi5cation. Biomass and Bioenergy 2001;20:45–6. [8] Senelwa K, Sims REH. Fuel characteristics of short rotation forest biomass. Biomass and Bioenergy 1999;17:127–40. [9] Rytter L. Nutrient content in stems of hybrid aspen as a1ected by tree age and tree size, an nutrient removal with harvest. Biomass and Bioenergy 2002;23:13–25. [10] Chinese National Bureau of Forest: LY/T 1211-1999. Field sampling and preparation of forest plant and forest Noor samples. Professional standard of forest of People’s Republic of China: LY/T 1210 ∼ 1275-1999. Chinese Standard Publisher, 1999. [11] Chinese National Bureau of Standards: GB 212-91. Proximate analysis of coal. National Standard of People’s Republic of China, 1991. [12] Chinese National Bureau of Standards: GB 5186-85. Testing methods for heat value of biomass fuels. National Standard of People’s Republic of China, 1985.
Chemical elemental characteristics of biomass fuels in China Liao Cuipinga; b;∗ , Wu Chuangzhia , Yanyongjieb , Huang Haitaoa a Laboratory
of Biomass Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Science, 81 Xianlie Zhong Road, Guangzhou 510070, China b College of Resource and Environment Engineering, East China University of Science and Technology, Rd. Meilong 130, Shanghai 200237, China Received 2 October 2002; received in revised form 10 November 2003; accepted 12 January 2004
Abstract This paper investigates the chemical elemental characteristics of 63 samples of biomass including agricultural biomass such as rice straw, wheat straw, corn straw, cotton straw and forestry biomass such as birch, spruce, willow, etc. in China. Twenty one di1erent biomass groups are distinguished as reference fuels in China. The elemental characteristics of bituminous coal are also presented for comparison. ? 2004 Elsevier Ltd. All rights reserved. Keywords: Biomass; Chemical elemental characteristics; Agricultural biomass; Forestry biomass
1. Introduction Biomass fuels are the 5rst energy source harnessed by mankind. They remain the primary source of energy for more than half the world’s population and account for 14% of the total energy consumption in the world [1]. Biomass is the most common form of renewable energy. The use of renewable energy sources is becoming increasingly important when it is considered to assist to alleviate global warming and provide fuel supply. In the past 10 years, there has been renewed interest, worldwide, in biomass as an attractive alternative to fossil fuels. Especially in developing countries, as it is readily available and when properly managed the resource is renewable and provides an indigenous fuel supply at lower cost. ∗ Corresponding author. Laboratory of Biomass Energy, Guangzhou Institute of Energy Conversion, Chinese Academy of Science, 81 Xianlie Zhong Road, Guangzhou 510070, China.
0961-9534/$ - see front matter ? 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.biombioe.2004.01.002
Using biomass as a source of fuel has little adverse environmental impact. The combustion of biomass produces signi5cantly less nitrogen oxide and sulphur dioxide than the burning of fossil fuels. Liquid biomass fuels like ethanol and methanol produce less carbon monoxide, hydrocarbons and potentially carcinogenic compounds than gasoline and diesel. Unlike fossil fuel combustions, the use of biomass fuels will not contribute to carbon dioxide levels that cause global warming. Biomass fuels are always the main kinds of energy resources except for coal in China. But they are used normally as a primary source of energy for domestic purposes in a low-eFciency way of combustion. In China, a total of 939 million tons of agricultural biomass residues produced each year and 551 million tons can be used as an energy resource, but only 266 million tons residues are used. With regard to forestry residues, there is a total 227 million tons yields in China of which 123 million tons are
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used [2]. With the implementation of R& D policy of sustainable energy of government, people realize the environmental bene5ts of biomass fuel. It is time to explore and utilize the biomass fuels in a clean and more eFcient way; however, there is a conspicuous lack of knowledge with regard to the chemical elemental characteristics of biomass fuels in China which is very important for utilization of them as energy sources. Modeling and analysis of energy conversion processes require adequate fuel characteristics especially average and variations in elemental compositions [3]. Knowledge of the concentration and speciation of alkali elements in fuels is useful for studies of BIGCC or other biomass power generation topics. The concentration and speciation of heavy metal elements is related to environment-related topics. With regard to the utilization of biomass as an energy source, the investigation of chemical elemental characteristics of biomass fuels is bene5cial for biomass fuels to 5nd suitable energy conversion technologies and for various energy conversion processes to utilize favorable biomass feedstock. Researchers in several countries have carried out extensive research to determine
the properties of their own available biomass resources [5–9]. In this paper, chemical elemental characteristics of biomass fuels are presented. The categories of biomass analyzed in this study are agricultural biomass and forestry biomass. 2. Sample collection 2.1. Sampling region Sample collection was based on the investigation of the distribution and quantity of biomass residues resource in China [2]. The samples were collected from the main production regions of straw and stalk such as East China, South China, North China and Northwest China, also from the regions with the highest forestry residues availability such as Northeast China and North China represented by Northeast China National Forest Region, Southwest China represented by Southwest China National Forest Region and South China represented by Southern Collective Forest Region. The sampling region can be seen in Fig. 1.
Fig. 1. Map of China with indications of sampling region on it.
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
2.2. Sampling type The agricultural biomass samples collected include traditional biomass fuels such as rice straw, wheat straw, corn cob, corn stalk, cotton stalk, peanut stalk, rape stalk, soybean stalk, sesame stalk, broad bean stalk, peanut hull, cotton shuck, etc. Forestry biomass samples collected include wood species such as birch (Betula), spruce (Picea asperata), willow (Salix), pine tree (Pinus tabulaeformis), poplar (Populus tomentosa), metasequois (Metasequoia glyptostroboides), phoenix tree (Paulownia catalpifolia) and fast-growing energy trees such as foliole eucalyptus (Eucalyptus) and rubber plants. The majority of these biomass species selected for the present study are among the highest yields. Although the wood fuels as pine, spruce, poplar, willow and birch are quite similar in composition, they were put in a separate group. The cluster analysis showed that the varieties are clustered to the same species group more than site, i.e. the e1ects of species are more important than that of growing regions. Chemical elemental characteristics of 21 di1erent groups are presented. Among them, there are eight groups that contain samples from only one region, in this situation; the data relating to these groups are presented with average values and without standard deviations. 2.3. Sample preparation and analysis Five kilogram of each sample was collected from the region and air dried, then ground twice and sieved to 200 mesh, and the 5nal analysis sample taken according to quartation. (LY/T 1211-1999)[10](LY/T 1211-1999 is professional standard that covers 5eld sampling and preparation of forest plant and forest Noor samples issued by Chinese National Bureau of Forest. This standard is issued under the 5xed designation LY/T 1211; the number immediately following the designation indicates the year of original adoption.) The analysis program includes proximate analysis of moisture, ash, volatile matter and the calculation of 5xed carbon according to GB212-91 [11] (GB212-91 is standard which covers the determination of moisture, volatile matter, and ash and the calculation of 5xed carbon on coals. This standard is issued under
121
the 5xed designation GB212; the number immediately following the designation indicates the year of last revision.); and the determining of calori5c value by WGR-1 calorimeter according to Chinese national standard (GB 5186-85 [12]: Testing methods for heat value of biomass fuels.); and ultimate analysis of C, H, O, N and S content for all samples by Elementary Vario EL. The chemical compositions of alkali metals and other ash-forming elements such as Al, Si, Ca, Fe, K, Mg, Na, P and trace elements such as As, Ba, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, Ti, V, Zn for all samples collected were analyzed. Samples were digested with 5:1 mixture of HNO3 : HClO4 and made up to 25 ml with high-puri5ed water derived from vaporizing of deionized water under boiling point and analyzed using ICP-Model IRIS 1000 ER/S (TJA Corp.). All analyses are performed on three repeats and averages presented. When the content is 10 ppm, the RSD is no more than 2%. The detective limits were carefully determined as triple standard deviation of blank. Three kinds of bituminous coal were also investigated for comparison. 3. Results and discussion 3.1. Proximate and ultimate analysis results The main material properties of interest of biomass as an energy source are also taken into investigation. Tables 1 and 2 list these characteristics of the reference fuels. Table 1 lists the moisture content, ash content, proportions of volatile matters and 5xed carbon together with calori5c value. Table 2 lists the elemental analysis of N, C, S, H and O. The reference biomass fuels are presented with their average characteristics compositions and standard deviations. Moisture content is of considerable importance with regard to selection of energy conversion process technology. Biomass fuels with low moisture content are more suited for thermal conversion technology while biomass fuels with high moisture content are more suited for biochemical process such as fermentation conversion [1]. On this basis, from Table 1, it can be seen that biomass fuels under this investigation are most favorable biomass feedstock for thermal conversion technologies with their moisture content in the range 6–10%.
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Table 1 Characteristics of the reference fuels—proximate analysis Group
Moisture (wt%)
Ash (wt% db)
Volatile matter (%)
Fixed carbon (%)
C.V (MJ/kg)
Rice straw Wheat straw Corn straw Soybean Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean stalk Rape stalk Foliole eucalyptus Rubber plant Willow tree Poplar Pine tree Spruce Phoenix tree Birch tree Metasequoia Bituminous coal
8:11 ± 1:51 8:63 ± 2:03 9:31 ± 2:05 9:34 ± 1:88 6:41 ± 2:81 7:66 ± 1:86 10.23 9:36 ± 0:41 8.56 7.66 7.62 6.15 6:5 ± 1:2 8:88 ± 2:27 9:08 ± 1:45 7:91 ± 1:65 8:61 ± 1:91 9:21 ± 0:5 7.74 9.06 7.38 2:83 ± 0:66
15:25 ± 2:64 12:45 ± 9:02 13:12 ± 8:79 6:08 ± 1:10 7:55 ± 6:91 6:41 ± 3:08 6.88 12:15 ± 3:02 9.12 6.11 5.03 3.60 5:55 ± 2:44 9:9 ± 3:31 6:17 ± 3:7 2:63 ± 0:87 0:89 ± 0:13 5:36 ± 2:33 5.28 2.36 2.20 20:08 ± 3:49
61:10 ± 2:51 63:96 ± 7:29 62:74 ± 6:15 68:95 ± 1:74 70:24 ± 6:43 67:36 ± 3:49 62.16 61:64 ± 1:9 66.67 68.93 68.44 72.99 67:75 ± 5:01 62:92 ± 5:59 69:2 ± 5:08 74:04 ± 0:36 76:50 ± 2:45 71:04 ± 3:26 68.68 74.91 74.30 28:33 ± 1:89
15:54 ± 1:36 14:96 ± 1:49 14:83 ± 2:13 15:62 ± 0:17 15:8 ± 1:85 18:57 ± 1:14 20.74 16:85 ± 0:71 15.66 17.30 18.90 17.26 20:19 ± 2:77 18:3 ± 1:44 15:55 ± 1:99 15:42 ± 1:14 14:45 ± 0:41 14:39 ± 5:09 18.29 13.68 16.11 49:08 ± 2:12
14:66 ± 0:71 16:56 ± 1:05 16:64 ± 0:38 16:96 ± 0:62 16:98 ± 0:64 17:91 ± 0:47 17.88 18:62 ± 0:21 15.75 15.92 16.31 16.65 19:33 ± 1:60 18:14 ± 1:30 18:79 ± 0:40 18:57 ± 0:17 19:38 ± 0:35 18:93 ± 0:71 17.96 19.34 19.62 34
Table 2 Characteristics of the reference fuels—ultimate analysis Group
N
C
S
H
O
Rice straw Wheat straw Corn straw Soybean Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean Rape stalk Foliole eucalyptus Rubber plant Willow tree Poplar Pine tree Spruce Phoenix tree Birch tree Metasequoia Bituminous coal
0:69 ± 0:21 0:58 ± 0:28 0:99 ± 0:20 0:95 ± 0:28 0:49 ± 0:12 1:09 ± 0:10 1.23 1:17 ± 0:09 2.06 0.81 0.97 0.23 0:50 ± 0:47 0:97 ± 1:04 0:77 ± 0:79 0:17 ± 0:06 0:10 ± 0:02 0:20 ± 0:10 0.70 0.16 0.11 1:13 ± 0:01
38:52 ± 1:03 42:11 ± 2:12 42:69 ± 1:47 43:16 ± 1:13 44:53 ± 0:50 46:10 ± 0:49 44.54 45:90 ± 0:54 40.28 41.34 42.16 42.42 50:15 ± 2:55 48:69 ± 1:69 46:79 ± 1:14 47:46 ± 0:45 49:41 ± 0:24 48:56 ± 0:25 48.14 48.32 47.98 63:78 ± 2:33
0:29 ± 0:17 0:32 ± 0:10 0:21 ± 0:13 0:20 ± 0:04 0:11 ± 0:05 0:26 ± 0:09 0.39 0:18 ± 0:05 0.28 0.29 0.24 0.27 0:02 ± 0:03 0:11 ± 0:09 0:30 ± 0:17 0:10 ± 0:09 0:05 ± 0:04 0:18 ± 0:17 0.04 0.20 0.08 0:97 ± 0:19
6:13 ± 0:49 6:53 ± 0:46 6:16 ± 0:81 6:9 ± 0:13 6:89 ± 0:10 6:85 ± 0:39 6.66 6:74 ± 0:27 7.18 6.57 6.13 7.06 7:45 ± 0:46 7:29 ± 0:60 7:10 ± 0:44 6:74 ± 0:02 7:67 ± 0:42 6:53 ± 0:52 7.88 8.36 6.82 3:97 ± 0:38
39:28 ± 2:14 40:51 ± 2:67 42:69 ± 2:11 44:76 ± 2:42 45:97 ± 1:51 43:35 ± 2:63 46.66 42:79 ± 0:05 42.47 45.16 45.28 46.10 39:64 ± 3:88 39:03 ± 3:25 40:60 ± 3:75 44:50 ± 1:36 42:19 ± 0:61 43:55 ± 1:55 39.84 40.60 43.98 10:08 ± 4:66
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The ash content of biomass a1ects both the handling and processing costs of the overall biomass energy conversion cost. The chemical compositions of the ash are closely related to operational problems such as slagging, fouling, sintering and corrosion. From Table 1, it can be seen that ash content ranged from 0.89–15.24% depending on biomass type. Forestry species have much lower ash content comparing with agricultural species. Volatile matter is in the range of 61–76%, forestry biomass has a somewhat higher volatile matter than agricultural biomass. While the ash content and volatile matter in bituminous coal is 20% and 28%, respectively. So, Biomass fuels have the advantages of low ash content and high volatile matter that make them the ideal feedstock for pyrolysis and gasi5cation. The elemental contents of N, C, S, H and O listed in Table 2 show clearly that these biomass fuels contain higher proportion of hydrogen and oxygen, compared with carbon, which reduces the energy value. It is said that carbon–oxygen and carbon– hydrogen bonds contain lower energy than in carbon–carbon bonds. So, the calori5c value of biomass is in the range of 16–20 MJ=kg. Forestry biomass fuels contain a slightly higher calori5c value than agricultural biomass. The calori5c value of bituminous coal achieves 34 MJ=kg, which is much higher than that of biomass. The lower content of nitrogen and sulphur in biomass fuels compared with coal is especially important for environment protection. 3.2. The chemical elemental characteristics of the reference fuels Table 3 shows some of the most important trace elements in the reference fuels. Table 4 shows the major elements (ash-forming elements) characteristics of the reference fuels. The data are presented as average values and standard deviations. 3.2.1. Ash-forming elements The ash-forming elements such as Al, Si (in this investigation only soluble Si is determined), Ca, Fe, K, Mg, Na and P in biomass are especially important for any thermochemical conversion process. The relatively high contents of alkali may lead to a serious technical problem when used as feedstock for
123
power production. It is generally believed that alkali metals are the main cause of slagging, fouling and sintering. In Tables 3 and 4, the 5rst 12 groups of the tables represent the agricultural biomass residues; the next nine groups represent forestry biomass. The tables show some clear di1erences among the fuel data for agricultural biomass residues and forestry biomass. From Table 4, it can be seen that the concentrations of Al, Si, Ca, Fe, K, Mg, Na and P in agricultural biomass fuels are generally higher than in forestry biomass, accounting for most of the top 10 high-concentration species of each element. Except Al, Si, Ca, Fe, Mg, P in rubber plant, Ca in willow, poplar and phoenix tree, Fe in foliole eucalyptus and willow, Na in foliole eucalyptus and spruce also belong to top 10 concentrations. In the same group, the content ranges from high to low as Ca, K ¿ Fe, Mg, P, Al ¿ Na, Si for almost all the agricultural biomass groups. Na in broad bean stalk and rape stalk is much higher than other elements but Ca. Al is much lower in these two groups than other elements but Si. The agricultural biomass residues contain much higher K than forestry biomass. K accounts for the 5rst high content in rice straw, wheat straw, corn stalk, corn cob, rape stalk and cotton stalk and cotton shuck. For forestry biomass, the sequence is Ca¿K¿Fe, Mg¿Al, P¿Na, Si, the exceptional case is that Na in foliole eucalyptus is larger than Mg, P and Al. Al in spruce tree ¿Mg. P in foliole eucalyptus ¿Al. The extreme properties of straw with respect to high potassium content are a major obstacle for an eFcient utilization of straw as a fuel for power production. 3.2.2. Trace elements It is seen that the content of most of the trace elements is higher in agricultural biomass than in forestry biomass. Foliole eucalyptus and rubber plant have relatively high content of these gaseous pollutant-forming elements because the samples of the two groups are the mixture of leaves, branches, trunks, roots and bark. According to our experiments, these elements in roots and leaves are much higher than in other parts of the trees. Some wood species also contain high amount of Cr, Cu, Mn, Zn. The amount of elements in the same group ranks from high to low approximately as Ti, Mn¿Ba,
As 5:327 ± 4:900 0:711 ± 0:567 1:627 ± 1:141 0:58 ± 0:31 1:080 ± 0:308 0:472 ± 0:147 0.750 1:123 ± 0:123 1.2509 1.2501 0.250 ND 1:001 ± 0:492 1:532 ± 1:889 0:594 ± 0:361 0:246 ± 0:002 0:249 ± 0:000 1.993 0.4250 0.25 0.24 14.5
Ba 72:1946 ± 36:9716 63:4064 ± 34:5446 24:7526 ± 21:1150 56:0804 ± 17:7757 24:5802 ± 16:1562 21:9475 ± 11:4834 19.887 49:7896 ± 22:0091 47.4082 72.3822 35.404 15.1159 0:6128 ± 0:3930 1:0623 ± 1:0052 23:3135 ± 16:8346 40:6391 ± 5:6746 52:1017 ± 16:5829 17:1434 ± 3:1438 ND 125.04 30.29 na
Cd 0:9206 ± 1:0268 0:4602 ± 0:4464 0:5540 ± 0:3904 0.28 0:3462 ± 0:2607 0:2766 ± 0:2285 0.300 0:3302 ± 0:2802 0.2752 0.3250 0.050 0.5497 0:1101 ± 0:0684 0:5916 ± 0:3440 0:8661 ± 0:9164 0.2916 0.14 0:1746 ± 0:0496 0.5301 ND ND 0.19
Group
Mo
Ni
Pb
Rice straw Wheat straw Corn stalk Soybean stalk Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean stalk Rape stalk Foliole eucalyptus Rubber plant Willow Poplar Pine tree Spruce tree Phoenix tree Birch tree Metasequoia
2:147 ± 1:360 3:443 ± 6:604 6:691 ± 11:420 2:508 ± 0:357 1:199 ± 0:436 2:001 ± 1:752 0:9005 1:634 ± 0:334 13.4594 2.9253 2.7753 4.1225 1:751 ± 1:886 5:690 ± 6:537 1:535 ± 1:466 ND 0.12 ND 1.5002 0.0996 ND
6:737 ± 9:841 10:105 ± 16:138 16:703 ± 29:044 2:478 ± 1:314 4:525 ± 3:043 5:611 ± 6:170 2.5515 3:069 ± 0:344 4.5282 2.3002 1.1501 0.5747 45:181 ± 50:122 60:312 ± 38:112 10:594 ± 14:781 1:821 ± 0:754 2:303 ± 0:933 0:887 ± 0:264 11.2511 2.3902 3.2926
25:01 ± 23:68 13:73 ± 7:77 14:36 ± 8:06 12:32 ± 7:39 63:18 ± 38:12 36:08 ± 55:63 25.0150 20:14 ± 8:39 23.7666 17.5018 13.0013 7.4955 8:46 ± 6:90 5:65 ± 3:14 10:97 ± 5:89 7:148 ± v3:203 5:166 ± 2:077 7:409 ± 2:156 0.7501 14.7147 9.9483
Bituminous coal*
na
13.9
20.9
Co 0:750 ± 0:242 1:088 ± 1:147 1:501 ± 1:709 0:557 ± 0:307 9:071 ± 11:278 0:521 ± 0:273 0.500 1:2097 ± 0:4096 1.2759 0.3750 0.225 ND 0:8054 ± 0:5305 1:7053 ± 1:0413 1:0343 ± 0:6555 0:6849 ± 0:2384 0:3361 ± 0:0621 0:3246 ± 0:0256 0.9251 0.92 0.56 8.5 Ti 38:61 ± 20:93 133:80 ± 195:42 213:69 ± 255:64 80:68 ± 73:56 92:47 ± 92:24 42:79 ± 26:30 61.7871 156:80 ± 68:53 126.3384 38.2538 15.2515 12.2427 60:06 ± 66:20 155:74 ± 119:93 47:45 ± 33:48 15:63 ± 7:50 10:02 ± 0:39 12:23 ± 6:73 45.0295 23.8024 29.2568 na
Cr 7:20 ± 4:30 11:70 ± 8:45 23:18 ± 21:57 3:41 ± 1:53 4:98 ± 2:34 4:94 ± 1:39 8.005 7:74 ± 0:48 5.2537 4.0004 3.500 2.2487 8:76 ± 8:92 12:79 ± 10:42 10:18 ± 8:09 7:68 ± 4:95 7:59 ± 3:61 3:00 ± 0:01 5.8006 9.71 12.23 36.8 V 1:786 ± 0:909 5:559 ± 6:738 9:356 ± 10:540 4:147 ± 4:200 5:406 ± 2:908 1:968 ± 0:836 2.8017 6:060 ± 2:984 3.0021 1.4251 1.6252 1.2742 1:996 ± 1:370 5:041 ± 4:722 1:794 ± 1:324 0:392 ± 0:119 0:386 ± 0:012 0:999 ± 0:127 1.8752 0.5478 0.9643 76.5
Cu 15:792 ± 9:510 65:886 ± 144:206 10:0482 ± 1:7546 9:3702 ± 0:9681 33:3247 ± 46:0969 13.508 14:0014 ± 0:2487 13.0091 23.0023 13.001 10.7436 35:020 ± 54:982 18:012 ± 9:120 76:481 ± 62:887 6:985 ± 1:131 6:423 ± 2:861 17:728 ± 3:969 8.2258 128.473 7.079 27.5 Zn 96:998 ± 96:417 29:357 ± 12:684 69:695 ± 67:355 11:963 ± 3:851 29:944 ± 12:091 24:592 ± 7:794 26.0156 29:494 ± 12:238 0.0000 13.2513 11.0011 12.9922 26:668 ± 15:341 89:231 ± 49:449 162:891 ± 130:758 68:613 ± 17:490 28:604 ± 17:667 14:920 ± 8:094 84.1084 108.6047 26.9991 na
Mn 1051:4858 ± 394:1487 94:5163 ± 55:1850 103:0021 ± 83:4222 68:3292 ± 26:9314 58:5857 ± 43:1590 48:1983 ± 30:3302 85.30 81:5926 ± 25:8314 87.8115 47.2547 28.75 24.7352 783:0643 ± 726:7773 507:0914 ± 397:1799 77:9378 ± 67:7102 29:8545 ± 2:5924 102:0932 ± 19:9297 124:0600 ± 69:5562 51.7552 81.217 17.121 na
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Rice straw Wheat straw Corn stalk Soybean stalk Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broad bean stalk Rape stalk Foliole eucalyptus Rubber plant Willow Poplar Pine tree Spruce tree Phoenix tree Birch tree Metasequoia Bituminous coal*
Group
124
Table 3 Characteristics of the reference fuels—trace elements (ppm)(dry biomass basis)
Group
Al
Si
Ca
Fe
K
Mg
Na
P
Rice straw Wheat straw Corn stalk Soybean stalk Corn cob Cotton stalk Cotton shuck Peanut shuck Peanut stalk Sesame stalk Broadbean stalk Rape stalk Foliole eucalyptus Rubber plant Willow Poplar Pine tree Spruce tree Phoenix tree Birch tree Metasequoia
967:36 ± 724:22 2052:36 ± 2459:83 4111:26 ± 4307:71 1336:36 ± 1012:86 2214:28 ± 2229:63 1243:65 ± 893:20 1796.0776 3037:49 ± 674:52 5001.0007 977.5978 450.0450 309.8141 707:42 ± 696:86 1900:12 ± 2398:09 753:06 ± 422:20 215:64 ± 62:09 120:65 ± 6:05 398:13 ± 10:40 595.0595 273.3791 457.4318
351:12 ± 217:73 170:10 ± 97:55 61:12 ± 71:72 14:66 ± 12:57 20:71 ± 14:55 12:31 ± 6:29 60.7865 62:10 ± 37:17 65.7961 12.2512 14.2514 6.4961 17:71 ± 9:74 67:14 ± 60:54 16:47 ± 19:35 1:6280 1:61 ± 1:61 3:99 ± 2:02 13.2513 5.7514 5.0329
4537:838 ± 1505:049 6527:8652 ± 3877:5945 9226:1746 ± 4213:4972 16159:4205 ± 1181:2845 9807:7677 ± 6793:7258 10347:4381 ± 6313:1003 9730.8385 10909:4207 ± 2745:2878 23301.3109 19351.9352 12823.7824 10773.5359 8787:7834 ± 5911:8360 11832:8977 ± 3680:1709 14591:4575 ± 7421:0828 13790:5867 ± 1905:7881 1757:2681 ± 187:4254 9331:7267 ± 7988:4207 12703.7704 7275.1718 5416.2747
1606:295 ± 896:084 2918:810 ± 3096:329 4867:475 ± 5159:783 1500:298 ± 899:227 3152:405 ± 3393:380 2383:605 ± 2213:734 1328.2970 4473:248 ± 2362:826 3982.7880 955.0955 670.0670 382.2706 1942:497 ± 1294:743 4017:759 ± 3242:818 1796:940 ± 1362:303 826:954 ± 497:276 673:203 ± 305:739 492:547 ± 42:277 2550.2550 935.6638 941.9097
21969:67 ± 8063:72 15659:31 ± 3718:68 14302:99 ± 7683:98 9986:00 ± 2773:25 14380:13 ± 4441:44 9086:181 ± 2716:262 9805.8835 9671:27 ± 819:506 6854.7984 12326.2326 5200.5201 10893.4639 4446:66 ± 4031:99 7421:92 ± 6365:41 7239:40 ± 5117:17 3250:32 ± 596:02 826:00 ± 19:79 1055:07 ± 579:79 6558.1558 2063.5395 1174.7413
2587:8107 ± 957:9750 2491:4973 ± 1308:8870 4767:2333 ± 2345:8982 7613:4081 ± 996:0624 2310:1995 ± 1316:9051 2507:6860 ± 1341:4089 4275.0650 3170:6482 ± 740:6622 10855.0986 3465.3465 2088.4588 1266.7400 938:6259 ± 926:0545 3292:4705 ± 2097:2242 2075:1650 ± 1619:3907 1145:9592 ± 60:4263 260:4646 ± 14:5752 305:4253 ± 55:5253 2161.2161 757.1457 507.5259
869:370 ± 609:402 319:167 ± 271:102 571:285 ± 674:656 161:251 ± 73:167 268:885 ± 81:924 718:527 ± 425:150 150.0901 176:120 ± 1:085 300.2101 275.0275 10051.0051 3497.9013 1090:447 ± 1181:92 242:047 ± 58:532 230:492 ± 182:779 70:035 ± 38:357 30:720 ± 14:721 248:565 ± 148:505 140.0140 44.0942 24.0593
1458:212 ± 536:016 1122:847 ± 1047:706 1849:333 ± 941:679 1559:032 ± 579:332 1299:590 ± 584:728 1815:397 ± 829:100 1665.9996 1391:651 ± 163:905 1828.7801 1605.1605 977.5978 342.2946 850:867 ± 588:926 1386:220 ± 1480:239 1005:410 ± 793:537 347:374 ± 119:485 91:882 ± 43:096 94:433 ± 11:884 1102.6103 210.7609 103.0574
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Table 4 Characteristics of the reference fuels—major elements (ash-forming elements)(dry biomass basis)
125
126
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Zn¿Pb, Cu¿Cr, Ni¿V, Mo, As¿Co, Cd in agricultural biomass and Mn, Ba, Ti, Zn¿ Pb, Cu, Cr, Ni¿ V, Mo, As, Co, Cd in forestry biomass. The content of Cl in biomass has not been studied in this investigation because of the limitation of analysis method. According to Nordin [3], the Cl content has a large variation of 0.008–0.74% dry basis. Faaij [4] found that Cl content is in a range of 0–1.1% dry basis, and the chlorine concentration vary widely between samples and a higher chlorine concentration can also be found close to the sea. 3.3. Composition range 3.3.1. Composition range of the biomass fuels in China Figs. 2 and 3 show the ranges of variation of various compositions that has been observed for the analyzed samples. The range found in composition data should be considered as indications of the possible variations caused by characterization procedures and the origin of the biomass samples [4]. Very wide ranges of the composition content of the biomass materials are found within the same biomass group and between groups. Tick marks in the 5gures present average values. Fig. 2 shows the composition content range of ash-forming elements for the reference fuels. A high K and Si contents is found in rice straw. Poplar, pine tree and spruce tree have the lowest K and Si content. A high K and Si contents have great a1ection on the power production from biomass. So rice straws are considered to be the unfavorable feedstock for power production. Ca content is especially high in willow tree and vary widely between samples. Na is extremely high in foliole eucalyptus and also varies widely between samples. Al, Mg, Fe are found to be high in corn stalk. Soybean stalk has the highest Mg content. Fig. 3 shows the content range of trace elements for the reference fuels. N and S as the most important elements with regard to the system emissions are also presented in Fig. 3. But comparing to coal, N and S content is much lower in biomass fuels than in coal (see Table 2). From Fig. 3, it can be seen that As, Cd, Mn, Zn in rice straw, Co, Pb in corn cob; Cr, Cu, Mo, Ti, V in corn stalk are high. Generally speaking, agricultural biomass fuels con-
tain higher heavy metal concentrations than forestry biomass fuels. Levels are high for Cd, S, N and Zn in willow wood. Foliole eucalyptus and rubber plants show high concentration of Ni, Mn and Cr. These trace elements, most of them, as heavy metals, have much inNuence on gas emission and ash composition characteristics. 3.3.2. Comparison with other studies on biomass compositional analysis A comparison with the studies of Nordin [3] and Sander [4] on biomass compositional analysis is showed in Table 5. Nordin presented compositions of a set of chemically well-characterized biomass reference fuels that were extracted from literature and some other sources of existing property data on biomass-related fuels. Bo. Sander gave the composition of straw and wood chips, which are the most abundant biofuels in Denmark. From the table, it can be seen that Si, Mg and Na are outlier in this paper compared to other studies; Si content is very small in this investigation because only soluble Si is determined. The groups investigated in this paper with the highest Mg and Na contents, which are an order of magnitude higher than in other groups, were sampled from Shanxi province; these two species were not included in studies of Nordin and Sander. They could be caused by the di1erence between species and the inNuences of growing conditions; but this remains to farther research. Comparing with the second highest contents of Mg and Na that are presented in parentheses, the ranges of most elements are comparable in this paper with Nordin. No signi5cant di1erences are observed. But the ranges of elemental compositions presented in Sander’s paper were much lower, because only two species in Denmark were investigated. This might also prove the di1erences between species.
4. Conclusions • Based on the experimental ber of biomass samples, are distinguished as the agricultural biomass and China.
data of a large num21 di1erent groups reference fuels of forestry biomass in
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Fig. 2. Composition content range of ash-forming elements for reference biomass fuels.
127
128
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
Fig. 2. continued.
L. Cuiping et al. / Biomass and Bioenergy 27 (2004) 119 – 130
129
Fig. 3. Composition content range of trace elements and N, S for reference biomass fuels.
• Biomass fuels have signi5cantly di1erent elemental characteristics compared with those of coal. It is clear that biomass fuels can reduce the environmental impact of burning fossil fuels to produce energy determined by their intrinsic properties. • Biomass fuels are composed of very heterogeneous constituents. Very wide ranges are found within the
same biomass group and between biomass groups for elemental composition content. Comparison shows that the ranges of elemental compositions presented in this paper are consistent with other studied in most elements. • Agricultural biomass contains much more ashforming elements and trace elements than most of forestry biomass.
130
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Table 5 Comparisons on biomass compositions Element
China
Nordin
Sander
Element
China
Nordin
Sander
N (wt%) C (wt%) S (wt%) H (wt%) O (wt%) Al (ppm) Si (ppm) Ca (ppm) Fe (ppm) K (ppm)
0.11–2.06 38.52–50.15 0.02–0.39 6.13–8.36 39.03–46.66 120–5001 1.6–351 (soluble) 1757–23301 382–4867 826–21969
0.12–3.1 44.0–58.8 0.009–0.26 5.7–6.3 32–46.2 19–2200 28–46000 650–16000 26–1600 400–25000
0.1–1.5 47–52 0.1–0.2 5.2–6.4
Mg (ppm) Na (ppm) P (ppm) Cu (ppm) Zn (ppm) Pb (ppm) Cd (ppm)
260–7613(10855) 24–3497(10051) 91–1849 6.4–128 11–162 0.75–63 0.05–0.92
160–1800 110–2000 75–2900 1.8–62 22–120 1.5–86 0.01–0.02
400–700 150–500 200–800
50–150 1000–8000 2000–4000 150–1000 1000–10000
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