Biochemical methane potential and anaerobic biodegradability of non-herbaceous and herbaceous phytomass in biogas production

Bioresource Technology 125 (2012) 226–232

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Biochemical methane potential and anaerobic biodegradability of non-herbaceous and herbaceous phytomass in biogas production Jin M. Triolo ⇑, Lene Pedersen, Haiyan Qu, Sven G. Sommer Institute of Chem. Eng., Biotechnology and Environmental Tech., Faculty of Engineering, University of Southern Denmark, Niels Bohrs Allé 1, DK-5230 Odense M, Denmark

h i g h l i g h t s " The Biochemical methane potential (BMP) of non-herbaceous phytomass was 159.3–249.5 CH4 NL kg VS

1

.

" Wood cuttings had half the BMP of lawn cuttings but a similar BMP to cow manure. " Wild plants showed a clear trend for lower biodegradability than lawn cuttings. " Lawn cuttings from gardens proved to be the most suitable substrate. " Lignin of 100 g kg VS

a r t i c l e

1

was the critical biodegradability point of phytomass.

i n f o

Article history: Received 2 July 2012 Received in revised form 16 August 2012 Accepted 18 August 2012 Available online 31 August 2012 Keywords: Lignocellulose Lignification Lawn waste Plant biomass Crystallinity

a b s t r a c t The suitability of municipal plant waste for anaerobic digestion was examined using 57 different herbaceous and non-herbaceous samples. Biochemical methane potential (BMP) and anaerobic biodegradability were related to the degree of lignification and crystallinity of cellulose. The BMP of herbaceous garden plants (332.7 CH4 NL kg VS1) was high, although lower than that of energy crops (400–475 CH4 NL kg VS1). Herbaceous wild plants from natural grassland contained most lignocelluloses, leading to relatively low BMP (214.0 CH4 NL kg VS1). Non-herbaceous phytomass had a high degree of lignification and a high concentration of crystalline cellulose, but due to the content of non-woody parts with a low concentration of lignocellulose the BMP was relatively high, 199.9 and 172.0 CH4 NL kg VS1 for hedge cuttings and woody cuttings, respectively. There were indications that a plant lignin concentration of 100 g kg VS1 is the critical biodegradability point in anaerobic digestion of phytomass. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction Biogas production is one of the most socio-economically costefficient renewable energy technologies, using organic waste and plant biomass as feedstock (Nielsen et al., 2002). It is also an efficient method of reducing greenhouse gas emissions (GHG) (Sommer et al., 2004; Dhingra et al., 2011). The European Commission has set mandatory national targets for renewable energy to account for 20% of energy consumption by 2020 and to reduce GHG emissions (EREC, 2010). In accordance with the European Commission targets, the Danish government has set a target for increasing the use of animal slurry as feedstock for biogas production from the current level (5%) up to 40% by 2020 (Green Growth, 2009). However, biogas production using only animal manure is not economically sustainable and addition of biomass from other sources is needed (Møller et al., 2007; Triolo et al., 2011). Energy ⇑ Corresponding author. Tel.: +45 4117 8867; fax: +45 6550 7354. E-mail address: [email protected] (J.M. Triolo). 0960-8524/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biortech.2012.08.079

crops have been widely used as co-substrate in Germany and Austria, particularly maize, sunflower, grass and Sudan grass (Amon et al., 2007). In Denmark industrial organic waste is co-digested with animal manure, but domestic sources of industrial organic waste have been exhausted and alternative biomass resources need to be explored (Møller et al., 2007; Raven and Gregersen, 2007). One source is imported organic industrial waste, which at present produces 0.68 petajoule (PJ) biogas in Denmark (Jørgensen, 2009). There is still the potential for 15.9 PJ biogas production from crop residues and municipal plant litter, which can significantly contribute to achievement of the Danish target on non-fossil fuel energy production. Cultivating energy crops for biogas production may not be viable due to production costs (Tilman et al., 2006; Raju et al., 2011). Moreover, there is a risk of increasing food prices if the area of agricultural land used for food and feed production is reduced (Hensgen et al., 2011). Herbaceous phytomass from natural grasslands, gardens and parks is cheap and use of this biomass for energy production would not affect food prices. However, the energy yield of such biomass is variable because the harvested plant

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material is diverse in terms of both plant species and organic composition. Furthermore, the biogas production potential may be low because the fibre content is high (Bühle et al., 2012). In Denmark, 557,000 tons of green garden waste are delivered annually to local municipal recycling centres. This corresponded to 17% of total household waste and 7% of total domestic waste in 2005 (Waste Statistics, 2005). The amount of garden waste increased 10-fold (96%) from 1994 to 2005 (Waste Statistics, 2005). Green garden waste consists of both herbaceous and non-herbaceous phytomass such as lawn grass, lawn weeds and residues from hedge and tree trimming, and is currently recycled after being composted and not used for biogas production (Hensgen et al., 2011). The reason could be that biogas plants are reluctant to use organic waste with a high content of lignocellulose, which is not easily transformed to biogas (Menon and Rao, 2012). However, since they are facing ‘‘aggressive biogas growth’’ with no available co-substrates, biogas producers are becoming increasingly interested in using herbaceous garden waste as a cheap feedstock. To our knowledge, no previous study has examined the biochemical characteristics of a wide range of green garden waste in terms of methane potential, anaerobic biodegradability and crystallinity of cellulose in order to assess the quality of this biomass as a feedstock for biogas production. Hence, in this study we investigated the biogas production potential of different forms of municipal herbaceous phytomass, as well as non-herbaceous material, i.e. green garden waste, energy crops, grass from natural grassland and woody waste. Biochemical methane potential (BMP) was determined and a distributional analysis was made of each organic component using data obtained from physicochemical analyses. These included Van Soest characterisation and determination of the crystallinity index of cellulose in different lignocellulosic materials using X-ray powder diffraction (XRPD). Anaerobic biodegradability was assessed using the concentration of lignocellulosic fibre in each biomass group and the BMP was correlated to the anaerobic biodegradability.

2. Methods 2.1. Biomass samples collected In total, 57 samples were collected from a wide variety of sources in Funen, Denmark, during the period July–October 2011 (Table 1). The samples obtained were separated into two groups, herbaceous plants that do not have a persistent woody stem and nonherbaceous material such as hedge and tree trimmings. The material was then subdivided into five groups: (1) herbaceous lawn waste from private gardens or public parks (‘lawn cuttings’); (2) hedge trimmings from the sites where lawn waste was collected (‘hedge cuttings’); (3) tree trimmings from the sites where lawn waste was collected and willow from wetland (‘wood cuttings’); (4) herbaceous plants from natural grassland (‘wild plants’); and (5) crops/crop residues from agricultural land (‘crops’). Most of the lawn waste consisted of lawn grass clippings and lawn weeds, e.g. smooth meadow-grass, clover, short bluegrass, etc. The hedge clippings were from common species such as oval-leaved privet and beech hedge and also contained hedge weeds. The tree trimmings were from birch and coniferous trees (Lawson’s cypress), as well plane trees from the roadside, and the willows from wetland included two dominant species in Denmark, namely weeping willow and sharpleaf willow. The hedge and wood cutting samples consisted of leaves, fruit bodies and branches around 20 cm in length. The wild plant samples from natural grassland were obtained from green areas beside roads or from wetland, for example, green areas beside streams and lakes, etc., and most

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were either perennial grasses or perennial flowering plants. The crop samples consisted of maize, sugar beet and wheat straw. Apart from grass samples, which consisted of relatively homogeneous leaves, all the other plant samples were heterogeneous and consisted of a distinct plant body such as stem, leaves, fruit bodies and occasionally branches. Hence, to improve analytical precision the samples were well homogenised by milling to a maximum size of 1 mm after drying at 60 °C prior to analysis. A control BMP test carried out on eight randomly chosen samples showed that the drying/milling process did not affect BMP and other biogas production characteristics (p > 0.05). On the other hand, from the repeatability test, the lower relative standard deviation was found in the dried/milled 2.61(±1.61)%, while that in fresh samples was much higher at 9.18(±8.19)%, showing that milling could improve the precision in BMP tests. 2.2. BMP assay The BMP of samples was determined according to VDI 4630 (2006) using 1.0-L (working volume) batch infusion digesters. Inoculum was obtained from the Fangel biogas plant, which operates at mesophilic conditions (37 °C), and is fed a mixture of 80% animal slurry and about 20% organic industrial waste. The inoculum was degassed for 2 weeks at 37 °C. The average pH of the inoculum was 8.1 and the volatile solids (VS) concentration was 67.3% of dry matter. The average methane (CH4) concentration in biogas released from the inoculum was 61.7%. When fermenting the plant residues, the inoculum:substrate ratio was set to 3:1 on a total solids (TS) basis. Following the recommendation in the standard protocol (ISO, 1995; VDI, 2006), 100 mL of anaerobic buffer solution with medium was added to the inoculum substrate mixture. Each reactor was flushed with nitrogen gas to ensure an anaerobic atmosphere. All assays were performed in triplicate. Fermentation was carried out under mesophilic conditions, at 37 °C. Digestion was terminated when daily biogas production per batch was less than 1% of cumulative gas production according to VDI 4630 (VDI, 2006), which corresponded to batch fermentation for approximately 60 days. A couple of times during a working day, the reactors were thoroughly mixed by hand shaking to avoid dry layers and to encourage degassing. The gas volume measured was corrected to a dry gas basis by excluding the water vapour content in wet biogas. Pressure and temperature for a norm litre (NL) of gas were corrected into standard temperature and pressure (STP) conditions (273 K, 1.013 hPa), according to VDI 4630 (2006). The CH4 concentration in the biogas was determined by a gas chromatograph (HP 6890 series), equipped with a thermal conductivity detector and a 30 mm  0.320 mm column (J&W 113-4332). The carrier gas was helium (30 cm/s), and injection volume was 0.4 mL. Injector temperature was 110 °C, and detector and oven temperature was 250 °C. Biomethane was quantified assuming that the dry biogas was composed of CO2 + CH4 alone. Consequently CH4 production volume was calculated according to VDI 4630 (2006) by multiplying the dry gas production by the CH4/CO2 + CH4 ratio. The BMP of cellulose (Avicel PH-101 cellulose) was determined as a control and inoculum as a blank. The BMP of cellulose was 393.3(±4.1) CH4 NL (kg VS)1 and the ratio of BMP to theoretical BMP (TBMP) was 94.8%. The TBMP of cellulose is 415 CH4 NL (kg VS)1. 2.3. Physicochemical analysis Dry matter (TS), volatile solids (VS), crude lipid (XL), total ammoniacal nitrogen (TAN = NH3 + NH4+) and total Kjeldahl nitrogen (TKN) were determined according to standard procedures

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Table 1 Phytomass samples included in the study, with cultivar and harvest date; L, lawn cuttings; H, hedge cuttings; W, wood cuttings; WP, wild plants; C, crops. No.

Type

Material

Latin name

Harvest

No.

Type

Material

Latin name

Harvest

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

L L L L L L L L L H H H H H H H H H W W W W W W W W W W

Meadow grass Meadow grass Meadow grass Meadow grass Grass mixture Grass mixture White clover Short bluegrass Short bluegrass Oval-leaved privet Oval-leaved privet Oval-leaved privet Ivy Beech hedge Black chokeberry Red chokeberry Ground-elder Ground-elder Birch tree Birch tree Birch tree Plane tree, fallen Plane tree, fallen Plane tree (green) Plane tree (green) Weeping willow Weeping willow Weeping willow

Poa pratensis Poa pratensis Poa pratensis Poa pratensis – – Trifolium repens Poa abbreviata Poa abbreviata Ligustrum ovalifolium Ligustrum ovalifolium Ligustrum ovalifolium Hedera canariensis Fagus sylvatica Aronia melanocarpa Aronia arbutifolia Aegopodium podagraria Aegopodium podagraria Betula Betula Betula Platanus Platanus Platanus Platanus Salix babylonica Salix babylonica Salix babylonica

July July October August July August October July July July October August August October October October July July October October October August October October October October October October

29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57

W W W W W W WP WP WP WP WP WP WP WP WP WP WP WP WP WP WP WP WP C C C C C C

Weeping willow Weeping willow Sharpleaf willow Sharpleaf willow Sharpleaf willow Cypress Northern bluegrass Green foxtail Bamboo Bamboo Common reed Common reed Tufted hair-grass Tufted hair-grass Reed canary grass Reed canary grass Reed canary grass Reed canary grass Reed canary grass Chrysanthemum Chrysanthemum Dandelion Dandelion Maize (grain) Maize (grain) Maize (leaves) Maize (leaves) Wheat straw Sugar beet

Salix babylonica Salix babylonica Salix acutifolia Salix acutifolia Salix acutifolia Chamaecypari lawsoniana Poa alpina Setaria viridis Bambuseae Bambuseae Phragmites Phragmites Deschampsia cespitosa Deschampsia cespitosa Phalaris arundinacea Phalaris arundinacea Phalaris arundinacea Phalaris arundinacea Phalaris arundinacea Helianthus salicifolius Matricaria chamomilla Taraxacum Taraxacum platycarpum Zea mays Zea mays Zea mays Zea mays Triticum aestivum Beta vulgaris

October October October October October October August July October October October October October October July October October August August July July July August July October July October October October

(APHA, 2005). Neutral detergent fibre (NDF) was determined according to Mertens et al. (2002). Acid detergent fibre (ADF) and acid detergent lignin (ADL) were determined according to ISO standards (ISO 13906:2009). Crude protein (XP) was determined by multiplying the difference between TKN and TAN by 6.25. Hemicelluloses, cellulose and lignin were determined in accordance with Van Soest characterisation for fibre analysis (Van Soest, 1963; Goering and Van Soest, 1970) using the results of NDF, ADF and ADL analyses. Hemicellulose was determined as the difference between NDF and ADF and cellulose by subtracting ADL from ADF. 2.4. XRPD analysis

(Mauseth, 1988; Triolo et al., 2011). Lignin is non-degradable and the content of lignin suppresses degradation of lignocellulosic fibres such as hemicellulose and celluloses (Triolo et al., 2011). Hence, TBMP is not used as a gauge of biogas production potential but as a yardstick to assess the biodegradability of substrate by calculating the ratio between BMP and TBMP, as in this study. Here the transformation of VS for bacterial growth was not taken into account, based on the assumption that microbial cellular yield is negligible. The theoretical CH4 production of each major component in the VS fraction was calculated using the stoichiometric equation (Symons and Buswell, 1933). TBMP (CH4 NL kg VS1) and anaerobic biodegradability were calculated using Eqs. (2) and (3), respectively, including lipid, protein, carbohydrate and lignin as g kg VS1 in the calculations:

The crystallinity of grass and woody biomass was compared using the crystallinity index (CI) determined by XRPD (Siemens D5000 Crystalloflex diffractometer). The X-ray unit was operated at 40 kV and 35 mA. The 2h region scanned was from 5° to 30°, with a step size of 0.02°. The CI of cellulose was calculated according to Park et al. (2010) from the height ratio of the intensity of the crystalline peak to the total intensity after subtraction of the background signal in the amorphous phase (Eq. (1))

where TBMP is expressed in CH4 NL kg VS1 and C57H104O6, C5H7O2N, C6H10O5 and C10H13O3 is the empirical formula for lipid, protein, carbohydrate and lignin, respectively, expressed as g kg VS1 (Triolo et al. (2011).

CI ð%Þ ¼ 100  ½ðI002  Iamorphous Þ=I002 

Anaearobic biodegradability ¼ ðBMP=TBMPÞ  100%

ð1Þ

where I002 is the intensity for the crystalline portion of cellulose at about 2h = 22 and Iamorphous is the peak for the amorphous portion at about 2h = 18.0.

TBMP ¼ ðC57 H104 O6  1014 þ C5 H7 O2 N  496 þ C6 H10 O5  415 þ C10 H13 O3  727Þ  0:001

ð2Þ

ð3Þ

All statistical analyses were performed using the SAS software package (SAS Institute, 1992). 3. Results and discussion

2.5. Data analysis 3.1. Specific methane potential In assessment of BMP, a simple stoichiometric calculation of the maximum potential for anaerobic gas production is used to assess the theoretical or stoichiometric methane potential (Møller et al., 2004; Raposo et al., 2011; Triolo et al., 2011). However, TBMP derived from the stoichiometric method is larger than actual methane potential, because recalcitrant carbon affects the latter

The mean concentration of CH4 in biogas from all samples was 56.6%, with very low variations between samples (standard deviation: 2.4%). Among the sample groups, CH4 concentration in biogas from lawn cuttings and crops was highest, 58.3(±1.1)% and 60.1(±3.7)%, respectively. As expected, crop samples showed the

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greatest methane production potential, approximately 5-fold greater than samples with the lowest methane production potential (Fig. 1 and Table 2). After crop samples such as maize and sugar beet, lawn cuttings gave the highest BMP of the biomasses tested, 288.7(±3.5) to 388.9(±10.2) CH4 NL kg VS1, which is at a similar level to the BMP of pig manure (Møller et al., 2004; Triolo et al., 2011). The BMP of the wild plants tested ranged from 104.0(±12.9) to 302.3(±6.1) CH4 NL kg VS1 (Fig. 1), and varied more than the BMP of the other biomass groups. The high variation in BMP and the large and variable amount of lignocelluloses in wild plants confirmed findings by Bühle et al. (2012), who demonstrated the problems of using grassland plants as feedstock for biogas production. A most interesting result in the present study is that some of the wild plant samples had lower BMP than the wood cuttings. Non-herbaceous plant samples produced less methane than the other groups but the production was still significant, ranging from 146.6(±12.0) to 249.5(±6.3) CH4 NL kg VS1 for hedge cuttings and 142.5(±15.3) to 239.9(±23.1) CH4 NL kg VS1 for wood cuttings. In terms of the different wood cuttings, BMP decreased in the order: birch > willow > plane tree. However, the differences in BMP between the different wood wastes were small compared with the variation within a particular wood type. Thus the standard deviation of the mean BMP obtained for birch cuttings was ±22.2, for willow cuttings ±4.7 and for plane tree cuttings ±31.6. Wood cuttings had approximately half the BMP of lawn cuttings but a similar BMP to cow manure (148–223 CH4 NL kg VS1; Møller et al., 2004; Triolo et al., 2011). The BMP of samples was influenced by time of harvesting, with summer (July–August) lawn cuttings having higher BMP than autumn cuttings (352.5(±27.8, n = 4) and 301.2(±102, n = 2) CH4 NL kg VS1, respectively). The wild plant material also showed a seasonal variation in BMP, with plants cut in October having low values and plants cut in July having higher BMP. The results were in accordance with the previous studies that reported seasonal decline of biogas production. The reason for decline is probably due to the advancing vegetation stage (Prochnow et al., 2009). The means of using the plant materials may cause significant seasonal fluctuation not only in energy efficiency, but also instability of the anaerobic environment in biogas reactors. Hence, a suitable rotation of feedstock against seasonal variations is necessary for optimal biogas operation. 3.2. Fractional lignocellulose and degree of lignification A major obstacle to using phytomass in biogas production is a high degree of lignification, which is a particular problem when

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using stem wood. Lignification is a physiological process influenced by genetic and environmental factors. The degree of lignification reflects the extent of lignin deposition in the plant cell well, which can be assessed either by the concentration of lignin in lignocellulose or the ratio of lignin to cellulose. Lignocelluloses were the most abundant organic compound in the samples tested here (Table 2 and Fig. 2). However, the concentration of lignocelluloses varied widely within the different plant groups tested. Lawn cuttings had a low lignocellulose content (50.7(±10.4)% of VS), owing to a larger proportion of non-cell wall components, and the concentration of lignin in lignocellulose was mostly very low (4.4(±2.4)% of VS), which is in good agreement with the BMP of this biomass. Wild plants had the highest content of lignocellulose (72.2(±3.9)% of VS) and their lignin concentration (15.2(±4.7)% of VS) was considerably higher than that of lawn cuttings. These differences are partly due to the different biochemical characteristics of the dominant plant community in natural grassland, but also to their greater age than lawn waste. Frequent lawn mowing shortens physiological vegetation age, which reduces the degree of lignification. The degree of lignification (lignin/lignocellulose) of herbaceous plant samples was low, 8.2% for lawn cuttings and 15.8% for wild plants. The lignocellulose concentration in non-herbaceous samples was low, 53.0(±12.7)% of VS for hedge cuttings and 50.6(±4.6)% of VS for wood cuttings. The low lignocellulose concentration of the non-herbaceous samples seemed to be due to a large amount of fruit bodies in these samples giving high methane potential and low lignocellulose concentration. In contrast, we found a very high degree of lignification, with lignin/lignocellulose comprising 29.4(±11.2)% of lignocellulose in hedge cuttings and 39.7(±7.5)% of lignocellulose in wood cuttings. 3.3. X-ray diffraction The access by hydrolytic enzymes to cellulose is affected not only by the degree of physical and chemical links between lignin and hemicelluloses in the plant cell, but also the crystallinity of cellulose. Hence, the low biodegradability of lignocellulosic biomass in an anaerobic environment is linked to lignin and biodegradability of the cellulose and hemicellulose included in a rigid structure of a lignocellulosic matrix and of crystalline cellulose. Cellulose is the most abundant fibrous fraction in lignocellulosic biomass and it is a high molecular weight linear polymer linked by b-1.4-glycosidic bonds. The amorphous and crystalline cellulose are caused by intramolecular and intermolecular hydrogen bonds (Park et al., 2010). The XRPD method used in this study is widely used

Fig. 1. Profile of measured BMP (CH4 NL (kg VS)1) for the different types of biomass tested. NL, norm litre (273 K, 1.013 bar). Error bars represent the standard deviation of triplicate values.

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Table 2 Organic composition, specific methane potential and anaerobic biodegradability (BD = BMP/TBMP  100%); NL = norm litre (273 K, 1.013 bar) of the different types of phytomass tested, DM = dry matter. Waste type Number of samples, n

Lawn cuttings n=9

Hedge cuttings n=9

Wood cuttings n = 16

Wild plants n = 17

TKN (g/kg DM) TAN (g/kg DM) NDF (g/kg DM) ADF (g/kg DM) ADL (g/kg DM) XL (g/kg DM) TBMP (CH4 NL kg VS1) BMP (CH4 NL kg VS1) BD (%) CH4 in biogas (%)

22.3(10.1) 1.86(1.51) 50.7(10.4) 30.1(4.8) 4.15(2.20) 7.38(2.94) 501.8(27.7) 332.7(38.4) 66.6(8.5) 58.3(1.1)

16.2(7.1) 1.70(0.80) 49.4(11.0) 39.2(10.7) 13.9(4.4) 4.39(3.50) 500.0(24.6) 199.9(40.8) 39.9(7.6) 54.7(2.0)

15.17(4.11) 1.74(1.20) 56.9(4.9) 44.9(4.5) 22.5(4.0) 3.70(3.10) 527.3(26.6) 172.0(28.9) 32.7(5.2) 55.6(1.6)

12.1(6.0) 1.17(0.84) 66.7(14.1) 43.8(8.1) 10.08(5.2) 3.09(1.47) 483.7(21.4) 214.0(58.1) 44.9(12.5) 56.4(1.2)

Fig. 2. (a) Mean organic composition of VS, (b) mean fraction of hemicellulose, cellulose and lignin in lignocellulose; and (c) mean lignocellulose concentration in lawn cuttings, hedge cuttings, wood cuttings, wild plants and crop samples. XL, crude lipid; XP, crude protein. Error bars represent the standard deviation within the sample group.

to compare crystallinity of cellulose by determining the relative differences between samples, but cannot be used to estimate the amount of crystalline and amorphous cellulose (Park et al., 2010). Here, 10 samples were randomly chosen and the crystallinity of cellulose measured using XRPD. The highest peaks for all the samples were found at 2h = 22° and the plane tree and willow samples show clearer and stronger peaks than grass samples, compared with the amorphous phase at around 2h = 18°. The cellulose crystalline peak of lawn grass was lowest of all samples (Table 3). The cellulose crystallinity index measurements (Table 3) showed that the low biodegradability of non-herbaceous

Table 3 Crystallinity index (CI) of selected lignocellulosic samples, determined by X-ray diffraction. Sample

Willow

Birch

Plane tree

Lawn

Reed canary grass

CI

43.0(4.2)

58.8(1.0)

52.0(2.8)

32.6(9.8)

44.4(5.3)

phytomass is caused not only by a high lignin concentration, but also by a low content of amorphous cellulose and a higher amount of crystalline cellulose.

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3.4. Anaerobic biodegradability Anaerobic biodegradability of the samples was calculated as the ratio between BMP and TBMP. It was possible to subdivide the phytomass into groups with high and low anaerobic biodegradability as related to lignin content and to the crystallinity of the cellulose in the biomass. Lawn cuttings (66.6(±8.5)%) and crops (77.8(±26.3)%) had a high anaerobic biodegradability, while hedge cuttings, wood cuttings and wild plants had a low anaerobic biodegradability, 39.9(±7.6)%, 32.7(±5.2)% and 44.9(±12.5)%, respectively. The influence of lignocellulose and lignin on biodegradability was examined by calculating the theoretical BMP of degradable fractions not containing lignin (TBMPDE) (Eq. (4)) and the TBMP of non-lignocellulose, defined as the theoretical BMP of neutral detergent soluble fractions (TBMPNDS) (Eqs. (4) and (5))

TBMPDE ¼ TBMP  TBMPLIGNIN

ð4Þ

where TBMPDE is the TBMP of degradable fraction (CH4 NL kg VS1) and TBMPLIGNIN is the TBMP of the lignin fraction (CH4 NL kg VS1)

TBMPNDS ¼ TBMP  TBMPNDF

ð5Þ

where TBMPNDS is the TBMP of the neutral detergent soluble components (CH4 NL kg VS1), which corresponds to the TBMP of nonlignocellulose, and TBMPNDF is the TBMP of neutral detergent fibre (CH4 NL kg VS1), which correspond to the TBMP of lignocellulose. Stoichiometric calculations of theoretical BMP using Eqs. (4) and (5) showed that the TBMP of most samples tested was around 500 CH4 NL kg VS1 and the variation within the tested samples was very low (Fig. 3). TBMPDE was much closer to measured BMP than TBMP, but still considerably higher than both. TBMPNDS of wood and hedge cuttings and wild plants was very similar to measured BMP, whilst that of lawn cuttings and crops was much lower than the measured values. Thus bioconversion to methane of organic components in hedge, tree and wild plant material almost corresponded to the amount of methane produced from non-lignocellulosic components in these plant groups. In contrast, BMP was much higher than the BMPNDS of lawn waste and energy crops, which could indicate that more lignocelluloses were transformed to methane due to a much lower degree of lignification and probably also due to lower crystallinity of cellulose. Measured BMP is presented in Fig. 4 as a function of lignin concentration in VS and lignin in lignocellulose. As can be seen from the diagram, the correlation between lignin concentration in VS and BMP was better (R2 = 0.761) when only data for crops and lawn cutting were used rather than all the biomass groups were included (R2 = 0.643). When BMP was plotted against degree of ligni-

Fig. 4. Biochemical methane potential (BMP) as a function of lignin concentration in VS (above) and as a function of lignin in lignocellulose (below): A, correlation when only data on crops and lawn cuttings were used; B, correlation when data on all the biomass groups were used.

fication, the R2 value decreased slightly to 0.720 (p < 0.05) with data for crops and lawn cuttings only, while that for all the biomass groups was much lower. Furthermore, there was no significant correlation between lignin and BMP from hedge cuttings, wood cuttings or wild plants. The BMP of crops and lawn cuttings was significantly affected by the concentration of lignin (Fig. 4). However, the BMP of hedge cuttings, wood cuttings and wild plants was more strongly related to the concentration of lignocellulose (Fig. 3), a plant component with a lignin concentration above 100 g kg VS1 (Fig. 2). There were indications that a plant lignin concentration of 100 g kg VS1 is the critical biodegradability point in anaerobic digestion of phytomass. 4. Conclusions

Fig. 3. TBMP, TBMPDE, BMP and TBMPNDS of lawn cuttings, hedge cuttings, wood cuttings, wild plants and crops.

Biochemical methane potential was low for phytomass with a lignin concentration above 100 g kg VS1 and high for phytomass with lower lignin concentrations. Despite its high degree of lignification and a larger amount of crystalline cellulose, the BMP of nonherbaceous phytomass was 159.3–249.5 CH4 NL kg VS1. The BMP of wild plant material displayed the largest variability between samples, but showed a clear trend for lower biodegradability and lower BMP than lawn cuttings. Lawn cuttings proved to be the most suitable substrate owing to their considerably higher BMP,

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