Biomassad Bimncrgy Vol. 5, NO. 1, pp. 95-111.1993 Printed io Great Britain. All rights rcsaved

0961-9534/93 $6.00 + 0.00 O1993PergmonPrwsLtd

BIOCHEMICAL METHANE POTENTIAL OF BIOMASS AND WASTE FEEDSTOCKS

D. P. CHYNOWETH,* C. E. TuRrcK. t J. M. OWENS,$ D. E. JERGER~ and M. W. F%cKp

* Agricukural Engineering Department, University of Florida, GainesviIle, FL 32611, U.S.A.

t Idaho National Engineering Laboratory, Idaho Fails, ID 83415, U.S.A. $ FuIl Circle Solutions Inc., Gainesville, FL 32601, U.S.A. 5 0. H. Materials Corporation, Findlay, OH 45839, U.S.A.

q Department of Genetics and Microbiology, AFRC In&tote of Food Research, Norwich NR4 7UA, U.K.

ABSTRACT

The biochemical methane potential (BMP)) assay was evaluated in terms of inoculum (rumen versus primary Sludge digester), inoculum-to-feed ratio, and particle size for analysis of extent and rate of conversion of biomass and waste feedstocks to methane. The rumen and sludge inocula exhibited similar solubilixation of particulate matter. An inoculum-to-feed ratio of 2:l was shown to give maximum conversion rates. particle size did not influence rate in the range of l-8 mm. An extensive data base on the biochemical methane potential of several biomass and waste feedstocks is presented, including freshwater, marine, herbaceous, and woody feedstocks and municipal wastes; data for plant part8 are also included. In addition, the influence of several parameters on the BMP of feedstocks are presented, including growth and harvest conditions, and ensiling.

KEYWORDS

Anaerobic digestion, biochemical methane potential, methane, biomass, wastes, renewable energy.

INTRODUCTION

Biomass and wastes represent a large potential energy resource that is renewable on a sustained basis. Decreasing energy supplies and environmental impacts associated with use of fossil energy forms are encouraging renewed interest in renewable energy. Biogasification of these organic fee&to& is an at&active option because:

- it can process wet or dry feeds - it does not require thermal or chemical pretreatment - it does not require pure cultures or sterile conditions - the product methane is high quality and easily separated from the reactor - the product methane can be used in a variety of states of purity and is commonly used as a

major energy form throughout the world

A method, referred to as the biochemical methane potential (BMF’) assay, was developed to estimate the ultimate conversion and associated methane yield of organic substrates.1 ‘This method has been widely applied with minor modification to determine the ultimate methane production from a variety of feedStOcks.2,3A,5,8,9,lo,12,12

95

96 D. P. CHYNOWETH et ~1.

Our laboratory has evaluated factors influencing this assay, including inoculum source, inoculum-to-feed ratio, and particle size. We have also applied a modified form of the assay to determine the extent and rate of conversion of a variety of feedstocks, including samples of marine, freshwater, herbaceous, and woody plants and several municipal and industrial wastes. Most of these assays were done in collaboration with overall biomass or waste systems studies to determine the technical and economic feasibility of production of methane from these feedstocks. The BMP assay has proved to be a relatively simple and reliable method for comparison of extent and rate of conversion to methane. These properties can be factored into an evaluation of biomass production and conversion systems, including feedstock selection; growth, harvest, and storage conditions; biogasification; gas use; and residue processing.

PRINCIPLES OF BMP ASSAY

nofw

The BMP assay was developed as a standardized method to determine the ultimate biodegradability and associated methane yield during the anaerobic methanogenic fermentation of organic substrates.) In general, it is analogous to the biochemical oxygen demand assay that has been widely used to determine biodegradability under aerobic conditions for water quality analysis. The test, described elsewhere in detaiL1v2 involves batch incubation of a substrate under conditions ideal for anaerobic decomposition. These conditions include: (1) broad spectrum inoculum; (2) excess inoculum; (3) excess nutrients; substrate concentration below inhibitory levels; (4) excess buffering capacity; (5) moderate temperature: and (6) strict anaerobic conditions.

For most of our assays we employed 100 ml culture volume, an inoculum from an active digester receiving domestic sewage sludge (primary), an inoculum-to-feed ratio of 2Jl (volatile solids basis), a feed concentration of 2 g/l (VS basis), and a mesophilic (35oC) temperature. Total gas and methane production were measured frequently (about twice per week) during the initial stages of the assay (2 weeks) and less frequently (biweekly) for the final stages (typically 46 days). Samples were run in duplicate or triplicate and controls included inoculum, cellulose, and standard biomass samples (napiergrass and poplar). The batch bottle reactors were incubated until no further gas production could be detected. At the end of each assay, solids analyses were conducted to provide data for mass balances.

Discussion of the validity of the BMP assay raises questions concerning factors influencing the assay and associated reproducibility among different laboratories. We examined three factors: inoculum source, inoculum-to-feed ratio, and particle size.

(Inoculum. In vitro dry matter digestibility (IVDMD) data, such as those presented by Moore and Bjomdah16, suggest that over 70% conversion of biomass in the rumen can take place in about 3 days compared to 30 days for similar conversion in a typical BMP assay using a sludge inoculum. The rumen data were obtained by measuring disappearance of suspended solids from fine-mesh nylon bags incubated in situ in a fistulated cow rumen, while the BMP results were determined by measurement of conversion of substrate to gas in BMP assays.

In order to evaluate this order-of-magnitude difference, experiments were conducted to compare digestibility of napiergrass by rumen and digester inocula using disappearance of suspended solids (coarse glass fiber filter), the procedure traditionally employed by the in vitro rumen assay, and gas production, the procedure used for the BMP assay. A typical plot of these experiments (Fig. 1) indicates that conversion versus time was similar and comparable to that typically reported for the rumen for the two inocula based on disappearance of suspended solids.

However, gas production in the digester or rumen samples could not account for the disappearance of suspended solids, suggesting that particles were reduced by physical and enzymatic action to a size not retained in the fine mesh bags. An alternative but less likely explanation for these results is that the particulate matter was converted to soluble refractory intermediates. Further research is needed (involving a careful accounting of solid, soluble, and gaseous carbon) to clarify the fate of the particles.

Biomass and waste feedstocks 97

70

10

0

I I I I I I I

A Cab. from gas prod. of BMP assa 0 Calc. from susp. rollds disapp.

A Calc. from susp. rollds dhapp.

20 40 60 80 100 120 140

Incubation Period (hours)

Fig. 1. Digestibility of napiergrass in rumen assay WDhlD) and digester fluid assay CbiochemicaJ methane potential assay)

- _ &j&Q. The inoculum-to-feed ratio (I/F) on the standard BMP procedure is approximately 1 .O (volatile solids basis). Previously the BMP assay was used to determine the maximum extent of biomass conversion.1*3*5 In order to use this assay to compare potential rates of conversion, it was important to determine that inoculum size is not limiting. Studies were initiated to determine the effect of increasing the inoculum-to-feed ratio on kinetics of methane production from cellulose, napiergrass, and energycane (sugar cane developed for high growth yields and low in soluble sugars) in order to optimize rates of hydrolysis and methane production in the BMP assays (Fig. 2). For cellulose, the BMP first order rate constants for methane production were slightly higher for the higher I/F ratios. Imbalance was documented by the presence of higher concentrations of volatile organic acids in the assays with the lowest I/F ratio. Data for the two biomass samples (energycane and napiergrass) were less conclusive. These data suggest that, for an estimate of the maximum rate of methane production using the BMP. increasing the I/F ratio may be needed for some types of substrates. These results confirm the similar conclusion by Tong et al.4 We therefore have modified the I/F ratio of the procedure to 2.0.

. . mBze). The standard procedure for processing samples was to grind them by passage through an Urschell Mill equipped with a 0.8 mm head. Others5 have dried samples and ball-milled them prior to analysis. Our goal was to find a particle size below which changes in conversion kinetics would be minimal. Our hypothesis was that particle sizes in the millimeter to centimeter range would not significantly expose more surface area and thus would exhibit similar kinetics. Tests with sorghum, energycane, and the organic fraction of solid waste (primarily paper) confirmed this hypothesis as shown in Fig. 3 and Table 1. We therefore routinely process samples for BMP studies through a 1.6 mm head. We think that particle size reduction below some size (about 1 mm) will begin to increase kinetics in an unreproducible manner, i.e. introduce an uncontrollable variable into the interpretation of kinetic constants from the assay. Smaller sizes would also be uneconomical to obtain on a comercial basis.

Met

hane

Y

ield

(L

/g

VS

ad

ded)

M

etha

ne

Yie

ld

(L/g

V

S

adde

d)

??

0 0

-L

iu

b ? P

I

I 1

Biomass and waste feedstocks 99

Table 1. Effect of particle size on biochemical methane potential of biomass and municipal solid waste

Feedstock and Size (mm)* B, (L 9-l VS) k (d-l)

MSW 0.8 0.22 0.17 1.6 0.22 0.21 3.2 0.24 0.15

12.7 0.23 0.16

energycane ball milled 0.8 8.0

0.32 0.085 0.24 0.065 0.29 0.085

wood (poplar) 0.003 0.8 8.0

0.33 __- 0.33 ___ 0.30 ___

sorghum 1.6 8.0

* size of exclusion head

0.41 ___ 0.42

INTERPRETATION OF BMF’ DATA

Like the profile of a BOD assay, the BMP assay generally adheres to first order kinetics. A typical curve obtained from triplicate samples of Napiergrass is shown in Fig. 4 with calculation of methane yield (BJ and conversion kinetic constant (k). BMP kinetic constants for primary sludge and water hyacinth were in reasonable agreement with those obtained by the more time consuming semi-continuously fed digester studies (Table 2). Finally, it is noteworthy that biomass feedstocks often deviate from this typical profile due to the presence of fast and slow digestible components (e.g. soluble and structural carbohydrates) and inhibitors. Examples of these profiles are shown in Figures 5 and 6 for wood and for the presence of a toxic pesticide. In general, we tend to emphasize the limiting (lower) kinetic constant for samples without inhibitors that exhibit two or more conversion phases.

Table 2. Comparison of kinetic rate. constants (d-l) determined by CSTR digester studies and biochemical metbane potential assays

Feedstock csTR* BMp**

primary sludge 0.124 0.136

water hyacinth 0.035 0.046

*semicontinuously fed continuously mixed reactor **batch biochemical methane potential assay

Met

hane

Y

ield

(L

/g

VS

ad

ded)

?

0 :, P

?

0 N

w

Met

hane

Y

ield

(L

/g

VS

ad

ded)

0 :, 9

P

??

h)

cd

P

Biomass and waste feedstocks

0

Kalthane 50 PPM Dtazanon 5 PPM Dlazanon 50 PPM Kelthane 5 PPM Dlazanon 5 PPM and Kelthano 5 PPM Feed Control

10 20 30 40

Incubation Period (days)

50

Fig. 6. Effect of pesticides on biochemical methane potential of water hyacinth

SUMMARY OF BMF’ DATA FOR BIOMASS AND WASTES

BMP analyses were conducted on numerous and a variety of feedstock samples for the following reasons:

(1) to compare the extent and rates of conversion of various feeds to methane (2) to compare the BMP of different varieties of the same species (3) to compare the BMP of different plant parts, e.g. leaves and stems (4) to determine the influence of growth conditions on the BME of the same variety (5) to evaluate the infhtence of post-harvest processing on the BMP of the same variety, e.g. ensiling, drying, and particle size reduction (6) to determine if a relationship can be found between organic composition and the extent and rate of conversion to methane

Most of these analyses were conducted in conjunction with other researchers involved in studies on production of the feedstock. Tables 3-9 summarize BMP values and conversion kinetic constants for samples analyzed recently in our laboratory.

Table 10 summarizes results from studies conducted recently. In general, some of the following general conclusions can be drawn from this work:

(1) Substantial differences were observed in methane yield and conversion kinetics with different species as well as within the same species (different clones, growth and harvest conditions). (2) Methane yields and kinetics increased with harvest frequency with napiergrass. (3) Methane yields and kinetics were generally higher in leaves than in stems.

102 D. P. CI-IYNOWJXH et al.

Sample Ultimate Methane Methane Production

Yield Rate Constant (L g-l vs)* (d-l)*

-EtzzY= - Rl Fresh - R2 40% moisture 40% moisture 20% moisture 20% moisture

Fresh - R-3 Fresh - R-2 40% moisture 40% moisture 20% moisture 20% moisture

- R-5 - R-10 - R-7 - R-4

- R-3 - R-8 - R-9 - R-5

. Studies

0.279 +/- 0.008 0.277 +/- 0.012 0.293 +/- 0.005 0.251 +/- 0.100 0.253 +/- 0.002 0.240 +/- 0.001

0.274 +/- 0.014 0.191 +/- 0.019 0.255 +/- 0.017 0.251 +/- 0.006 0.231 +/- 0.012 0.247 +/- 0.019

0.097 +/- 0.004 0.071 +/- 0.002 0.105 +/- 0.039 0.051 +/- 0.003 0.089 +/- 0.066 0.070 +/- 0.035

0.126 +/- 0.073 0.155 +/- 0.123 0.073 +/- 0.008 0.051 +/- 0.003 0.086 +/- 0.037 0.074 +/- 0.028

. sh anded ws Study

Fresh energycane 0.245 +/- 0.001 0.112 Ensiled

+/- 0.039 energycane 0.265 +/- 0.010 0.072 +/- 0.003

Fresh napiergrass PI300086 0.260 +/- 0.019 0.062 +/- 0.007

Ensiled napiergrass PI300086 0.310 +/- 0.011 0.106 +/- 0.042

Fresh pearl millet 0.257 +/- 0.022 0.064 +/- 0.012 Ensiled pearl millet 0.304 +/- 0.017 0.087 +/- 0.012

Fresh X-14 0.278 +/- 0.011 0.090 0.038 Ensiled X-14

+/- 0.329 +/- 0.012 0.095 +/- 0.058

Fresh napiergrass (A) 0.248 +/- 0.008 0.059 Fresh napiergrass (B)

+/- 0.005 0.257 +/- 0.003 0.061 0.001

Ensiled napiergrass +/-

0.264 +/- 0.017 0.074 +/- 0.008

* Mean +/- 80% Confidence Interval (o-0.10)

Sample Ultimate Methane Methane Production

Yield Rate Constant (L g-l)* (d-l)*

Alemangrass 6A Alemangrass 7A

Paragrass 1P Paragraso 3P

Bun-long taro corm Bun-long taro top Chi-Sen tar0 corm Chi-Sen tar0 top

0.298 +/- 0.002 0.293 +/- 0.008

0.242 +/- 0.015 0.238 +/- 0.012

0.355 +/- 0.050 0.314 +/- 0.020 0.344 +/- 0.012 0.321 +/- 0.015

Saccharum robusttam 0.281 +/- 0.013

mcaUgnAn m "B" Erianthus V"

0.297 +/- 0.056 0.266 +/- 0.033 0.267 +/- 0.004

Sugarcane hybrids US72-1288 US84-1008 US8401009 US84-1018

0.277 +/- 0.038 0.261 +/- 0.018 0.292 +/- 0.007 0.251 +/- 0.009

0.118 +/- 0.013 0.146 +/- 0.063

0.134 +/- 0.066 0.087 +/- 0.005

0.218 +/- 0.003 0.245 +/- 0.010 0.250 +/- 0.178 0.059 +/- 0.015

0.050 +/- 0.002

0.060 +/- 0.002 0.060 +/- 0.002 0.070 +/- 0.002

0.090 +/- 0.061 0.075 +/- 0.015 0.080 +/- 0.002 0.060 +/- 0.002

Effect ofHarvest

Napiergrass PI300086 3 times/yr 0.294 +/- 0.045 0.07 +/- 0.02 2 times/yr 0.258 +/- 0.027 0.10 +/- 0.01 1 time/yr 0.238 +/- 0.006 0.13 +/- 0.01

Napiergrass Mott (N-75) 3 times/yr 0.291 +/- 0.034 0.08 +/- 0.03 2 times/yr 0.249 +/- 0.030 0.13 +/- 0.02 1 time/yr 0.221 +/- 0.011 0.13 +/- 0.01

Energycane L79-1002 3 times/yr 0.294 +/- 0.036 0.08 +/- 0.03 2 times/yr 0.261 +/- 0.022 0.09 +/- 0.01 1 time/yr 0.246 +/- 0.005 0.11 +/- 0.01

* Mean +/- 80% Confidence Interval (a=O.lO)

104 D. P. CHYNOWETH et ~1.

(4) Ensiiing did not have a significant influence on methane yields or kinetics. (5) Methane yield could not be correlated to any single compositional characteristic, including cellulose, hemicellulose, lignin, cell content, total cell wall, crude fiber and acid detergent fiber and in vitro dry matter digestibility(IVDMD). (6) Analysis of the relationship of methane yield and kinetics to combinations of the above chemical characteristics shows promise and is in progress.

Table 5. Biochemical methane potential of Surgassum

Sample Ultimate Methane Methane Production

Yield Rate Constant (L g-l)* (d-l) *

Saraassum Growth-Temnerature Study .

S ?? flp.atans 15 c 24” C 3o” c

0.032 +/- 0.008 0.068 +/- 0.004 0.073 0.005 0.129 0.046 +/- +/- 0.072 +/- 0.010 0.190 +/- 0.042

8. r>tFroDleuron 15 c 0.077 24O C

+/- 0.005 0.081 +/- 0.005 0.091 0.004 0.101 0.022

30” c +/- +/-

0.067 +/- 0.005 0.165 +/- 0.037

Saraassum MorPholoaical Study

Si futang Bladders Blades Stipe Whole plant

0.178 +/- 0.019 0.118 +/- 0.096 0.143 +/- 0.005 0.123 +/- 0.120 0.182 +/- 0.024 0.082 +/- 0.076 0.165 +/- 0.011 0.061 +/- 0.041

0.171 +/- 0.005 0.097 +/- 0.001 Blades 0.148 +/- 0.010 0.102 +/- 0.014 Stipe 0.119 +/- 0.005 0.150 +/- 0.010 Whole plant 0.145 +/- 0.002 0.089 +/- 0.008

* Mean +/- 80% Confidence Interval ( a= . 0 10)

Table 11 lists BMP results for samples of biomass analyzed both at the Institute of Gas Technology and the University of Piorida in decreasing order of ultimate BMP value. These upper values are not substantially different and are approximately equal to the value obtained from cellulose. The lower values for each of the groups show greater differences reflecting factors such as the presence of more lignin in some samples (which is refractory to anaerobic decomposition) or the presence of inhibitors (e.g. tannins and resins found in soft woods).

Table 12 lists BMP results by various categories of interest. Highest BMP values were obtained for wastes and vegetable oil. This may be attributed to the high H/C ratio of these fat rich samples and their high degree of biodegradability. Extremely low values were obtained for eucalyptus, pine, and newsprint. These may be a result of the presence of inhibitors or the inaccessibility of the cellulose in the lignocellulosic complex.

We are in the process of evaluating the validity of a correlation of extent (B,) and rate (k) of the BMP of samples for which chemical analyses exist with: organic matter, cellulose, hemicellulose, lignin, cell content, total cell wall, crude fiber, and acid detergent fiber, and IVDMD. This analysis is incomplete; however, preliminary results suggest that no correlation exists between the extent of conversion and any

Biomassandwastefeedstocks 105

ofthese parameters exceptlignin.There appears to be acorrelation between the rate ofconversion and lignincontent.

Table6.Biochemicalmethanepotenrial ofenergycane (commercial SuccharumCR56-8 X Tiunum96 from Argentina)

Sample Ultimate Methane Methane Production

Yield Rate Constant (L g-l)* (d-l)*

g ,

0.726 cm 0.276 +/- 0.010 0.085 +/- 0.009 0.0726 cm 0.228 +/- 0.011 0.065 +/- 0.019 Ball Milled 0.298 +/- 0.011 0.147 +/- 0.093

. . . E.zv==ane - Nltroaen Fe&llzer Stub!

no addition 0.299 +/- 0.019 0.094 +/- 0.017 150 lb/acre 0.279 +/- 0.007 0.082 +/- 0.045 300 lb/acre 0.261 +/- 0.014 0.073 +/- 0.016

* Mean +/- 80% Confidence Interval ( a= . 0 10)

Table7.Biochemicalmethanepotentialofseveraifeedstocks

Sample Ultimate Methane Methane Production

Yield (L g-Q*

Rate Constant (d-l)*

Turf grass Floritum St. Aug. 0.332 +/- 0.033 Seville St. Aug.

0.120 +/- 0.004 0.247 +/- 0.005 0.110 +/- 0.065

Food waste 0.541 +/- 0.032 0.232 +/- 0.004 Sorghum 0.311 +/- 0.011 Water hyacinth

0.152 +/- 0.017

(High lignin) 0.196 +/- 0.004 0.091 +/- 0.015 Water hyacinth

(Low lignin) Microalgae

0.213 +/- 0.005 0.110 +/- 0.022 0.183 +/- 0.001 0.172 +/- 0.111

MSW non-classified 0.210 +/- 0.012 0.152 +/- 0.051 MSW non-classified 0.220 +/- 0.009 0.132 +/- 0.004 MSW feed 429-ETU 0.292 +/- 0.018 0.256 +/- 0.151 MSW 0.0762cm (.03") 0.206 +/- 0.014 0.172 +/- 0.015 MSW 0.0381cm (.06") 0.212 +/- 0.010 0.214 +/- 0.057 MSW 0.3175cm (.125") 0.224 +/- 0.002 0.152 +/- 0.097 MSW 1.27cm (.5") 0.216 +/- 0.015 0.156 +/- 0.017

* Mean +/- 80% Confidence Interval ( a= . 0 10) ** BMP assays of MSW were funded by SERI.

106 D. P. CHnrovm’m et al.

Table8.Effectofplaotpertandgenotypeonbiochemicalmethanepotentialofnapiergrass

Sample Ultimate Methane Methane Production

Yield Rate Constant (L Q-l)* (d-l)*

PI300086 whole plant leaves stems

N-51 whole plant leaves stems

N-75 whole plant leaves stems

S42 whole plant leaves stems

s41 whole plant leaves stems

s44 whole plant leaves stems

23a x 300086 whole plant leaves stems

285 whole plant leaves stems

551 whole plant leaves stems

0.243 +/- 0.003 0.10 +/- 0.01 0.262 +/- 0.001 0.09 +/- 0.02 0.242 +/- 0.001 0.08 +/- 0.01

0.263 +/- 0.010 0.07 +/- 0.01 --- MB_ B-B WV_ _-- M-B W-W B-B

0.296 +/- 0.025 0.13 +/- 0.02 0.284 +/- 0.035 0.15 +/- 0.01 0.298 +/- 0.015 0.11 +/- 0.01

0.322 +/- 0.035 0.08 +/- 0.01 --- --- -WV W-M MB_ L-W B-W B-B

0.305 +/- 0.036 0.08 +/- 0.01 0.311 +/- 0.037 0.08 +/- 0.01 0.272 +/- 0.025 0.08 +/- 0.01

0.304 +/- 0.019 0.10 +/- 0.01 0.306 +/- 0.006 0.15 +/- 0.01 0.287 +/- 0.029 0.10 +/- 0.02

0.321 +/- 0.009 0.07 +/- 0.01 0.297 +/- 0.002 0.09 +/- 0.01 0.251 +/- 0.075 0.05 +/- 0.01

0.278 +/- 0.033 0.09 +/- 0.01 0.274 +/- 0.006 0.09 +/- 0.01 0.281 +/- 0.044 0.07 +/- 0.01

0.342 +/- 0.023 0.09 +/- 0.01 W-B --- W-W B-B W-B M-W W-W B-B

* Mean +/- 80% Confidence Interval (a=O.lO)

Biamassandwastefeedstocks 107

Wood species Ultimate Methane Methane Production

Yield Rate Constant (L g-l)* (d-l)*

Cellulose (control)

u (willow) (163)U* erioca

S. (183)U S. (242)~

. S. lucid (1251) U S. lu& (2244) U S. lucidq (3247) U

S. exicfua (2164) U S. exiqyg (2181) U S. exicua (3181) U

$. al& var m (SA2)F

S. alba (SA22) F

0.39 (0.05)

0.29 (0.01)

0.31 0.27 I:%; .

0.29 (<O.Ol) 0.27 (0.01) 0.27 (<O.Ol)

0.27 (~0.01) 0.28 (0.01) 0.31 (CO.01)

0.24 (<O.Ol) 0.22 (CO.01)

0.18 (0.02) 0.19 (0.02)

S. ouzpureg(SP3)F-1988 0.14 S. Durl;lureg(SP3)U-1988 0.16

. rIXIrea(SP3)-1986 0.23 . Se amWoides (SAM3)F 0.25 .

S- a~v~daloldes (SAMS) 0.21

S. (SH3) F 0.27 astata (SH2) 0.23

l?r) ,*ara WlCZJJ , 0.28

0.28

0.29

p.x euramericu(DN30)'0.28 P.x eurmricu(DN30)d0.24 P.x euramericana(DN33)'0.28 P.x euramericanq(DN33)d0.26

(0.01) (0.02) (0.01)

(<O.Ol) (0.02)

(0.01) (0.01)

(c0.01)

(0.02)

(0.01)

(KO.01) (0.01)

(c0.01) (CO.01)

0.18 (0.02)

0.02 (X0.01) 0.03 (<O.Ol) 0.02 (<O.Ol)

0.02 (X0.01) 0.02 (X0.01) 0.03 (<O.Ol)

0.01 (c0.01) 0.01 (CO.01) 0.01 (<O.Ol)

biphasic biphasic

biphasic biphasic

0.12 (c0.01) biphasic

0.04 (X0.01)

biphasic 0.04 (<O.Ol)

biphasic 0.04 (CO.01)

biphasic

biphasic

biphasic

biphasic biphasic biphasic biphasic

108 D. P. CHYNOWETH et al.

Table 9. (continued)

pol>ulus SP* 0.27 (0.04) biphasic . P. deltoides 0.22 (0.02) biphasic

0.32 (0.01) biphasic

0.24 (<O.Ol) biphasic J&uid- (sweetgum)

stvraalug 0.21 (dO.01) biphasic

* Values in parentheses = standard deviation. 8Clone designations appear in parentheses with harvested

year (for S. n-urea F= fertilized treatement; U= unfertilized treatment.

bClone NM5. "First year growth. dSecond year growth. *Third year growth.

Table 10. List of biochemical methane potential analyses associated with biomass growth studies

Study Source No. Samples* Ref

Energycane and napier- grass drying study

Energycane particle size

Effect of ensiling

Flooded soil crops

Saruassum composition

Napiergrass harvest freq.

Napiergrass: genotype, size, plant parts

Turf grasses

Woods

Municipal solid waste

(Sorghum, run at IGT

Other samples (UF only)

Total (UF only)

Mislevy

BERL 4

Prine/Woodard 15

Snyder 32

Bird 16

Prine/Woodard 72

Schank

Uudeck

White/Zuffa/ Ranney

Various Sources

Texas A&M

12

43

2

33

15)

50

294

(7)

(8)

(9)

(14)

(11)

__

(2)

(12,131

(10)

* All samples were run in duplicate or triplicate with inoculum, cellulose, and biomass controls

Biomass and waste feedstocks 109

Tablell.Rangeofbiochemicalmethanepotentialdataforbiomassofwastefeedstocksofwhichseveralsamples wexeanalyzed

Sample B, k

L g-l vs

Kelp (mrocvstb)

Sorghum

SSUlQ

Napiergrass

Poplar

Water hyacinth

Sugarcane

Willow

MSW

Avicel Cellulose

0.39 - 0.41

0.26 - 0.39

0.26 - 0.38

0.19 - 0.34

0.23 - 0.32

0.19 - 0.32

0.23 - 0.30

0.13 - 0.30

0.26 - 0.28

0.20 - 0.22

0.37

0.05 - 0.16

0.09 - 0.11

0.05 - 0.16

0.01 - 0.04

0.13 - 0.16

0.14

Table 12. Summary of biochemical methane potential ranges of several biomass and waste samples

Sample L g-l vs

All samples

All seaweeds

All grasses

All woods

Samples with high values

Vegetable oil 0.94 Primary sludge 0.59 Food waste 0.54

Samples with low values

Eucalyptus 0.014 Pine 0.059 Bambo 0.016

0.014 - 0.94

0.26 - 0.40

0.16 - 0.39

0.014 - 0.32

0.37 Avicel cellulose

110 D. P. CHYNOWETH et al.

SUMMARY AND CONCLUSIONS

The biochemical methane potential is a valuable method for determination of the potential extent and rate of conversion of biomass and waste feedstocks to methane. It can be used in lieu of the more expensive and time-consuming technique of using semi-continuous feed bench-scale digester studies. The results of this assay can be used to compare differences in extent and rate of BMP as a function of species or waste type, variety, growth and harvest conditions, and post-harvest treatment. A good broad spectrum inoculum such as effluent from an active domestic sludge digester is suitable. Inoculum from a presumably more active cellulolytic environment such as the rumen did not exhibit better extent or rate of conversion. In order to use the assay for comparing kinetics of conversion, it is important to employ an I/F ratio of 2.0 or greater and use particle sizes greater than the millimeter range. Lignocellulose biomass samples from the categories of marine, freshwater, herbaceous, and woody species exhibited similar upper levels of conversion. However, substantially different values were obtained for different samples of the same species depending on the variety, harvest, and growth conditions. Post-harvest conditions such as ensiling or drying did not have a substantial effect on the BMP values normalized to a weight basis. However, it should be recognized that post-treatment options vary significantly with respect to losses from field to digester. For example, drying and baling result in greater total mass losses than ensiling even though the BMP yields (volatile solids basis) of processed biomass are similar. Correlations could not be found between specific organic components and BMP results. We are beginning to evaluate extent and rates of conversion as a function of multiple component analysis.

ACKNOWLEDGEMENTS

The authors wish to acknowledge numerous researchers identified in Table 12 for providing well documented biomass samples for analyses. Dr. John Moore and associates are acknowledged for organic component analyses of biomass samples. In addition, we thank the Gas Research Institute (Contracts 5080-260-1303 and 5086-226-l 199) and U.S. Department of Energy/Solar Research Institute (Contract XL-g-1 8036-3) for support of this research.

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