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Methane production and kinetic modeling for codigestion of manure with lignocellulosic residues Muhammad Awais, Merlin Alvarado Morales, Panagiotis Tsapekos, Muhammad Gulfraz, and Irini Angelidaki Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02105 • Publication Date (Web): 26 Oct 2016 Downloaded from http://pubs.acs.org on October 28, 2016
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Methane production and kinetic modeling for codigestion of manure with lignocellulosic residues 1
Muhammad Awais, 2Merlin Alvarado-Morales, 2Panagiotis Tsapekos, 1Muhammad Gulfraz and
2
Irini Angelidaki*
1
Department of Biochemistry, PMAS-Arid Agriculture University Rawalpindi, Pakistan
2
Department of Environmental Engineering, Technical University of Denmark, 2800 Kongens
Lyngby, Denmark
ABSTRACT Anaerobic digestion (AD) of animal manure and lignocellulosic residues is gaining increased interest due to their wide availability, optimum physicochemical characteristics, high methane potential and absence of conflict with human food chain compared to energy crops. The aim of this study was to assess the biomethanation process of two lignocellulosic substrates, wheat straw (WS) and meadow grass (MG), with cattle manure (CM) under thermophilic (53°C) conditions focusing on nutrients availability in the reaction mixtures along with C/N ratios. Results showed that using 50% WS on organic matter basis in the feedstock and substituting the rest of volatile solid (VS) component share between CM and MG (25/75, 50/50 and 75/25), the methane yield can be increased by 20-24% compared to WS mono-digestion with a methane ,production rate of 27, 23 and 22 NmLCH4/gVS/d respectively. Moreover, the positive effects of coupled biological reactions in the reaction mixture of co-digestion were explained by using the synergistic effect value (η). The η value was calculated by using estimated and experimental methane yields. Furthermore, in MG co-digestion where 75% of the VS originated from MG and
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rest was distributed as 25/75 mixture of CM and WS showed 14% enhancement in methane yield compared to MG mono-digestion with the maximum methane production rate of 25 NmLCH4/gVS/d in batch experiments. Finally, the best co-digestion results with highest methane yield (up to 25%) and lowest lag phase (6-7 days) were achieved when 75% of organic matter was originated from CM. The combination presenting the above mentioned increase in methane yield also showed a methane production rate of 22 NmLCH4/gVS/d. It was concluded that increasing the MG share in co-digestion improves the feedstock digestibility and also gives the higher methane production rates. In contrast, high WS share increases the lag phase and detriments the biodegradability. Finally, through co-digesting two lignocellulosic substrates of different physicochemical characteristics with cattle manure, the overall biodegradability as compared to single substrate digestion is improved and the methane yield is enhanced. INTRODUCTION In the past, the common usage of manure was to be applied as fertilizer, which can have adverse environmental impact, in terms of terrestrial eutrophication and greenhouse gases emissions. Nowadays, a solution applied for wastes and residues is to treat them with simultaneously recovery of energy, through anaerobic digestion (AD). The use of manure in Denmark is well established for biogas production, as 40 million tons of manure are available for AD every year.1 To further shift towards these substrates for AD, the Danish Green Growth strategy has also been intended to exploit 50% of livestock manure by the end of 2020.2 Due to their availability, high biomass production rates, and no competition with human food, lignocellulosic substrates are suitable candidates for biogas production. For example, grasses covering 26% of total world land, growing more rapidly than trees, using less ground water and growing on non-cultivated land are potential substrates for biofuels production.3 In parallel, tremendous amounts of wheat
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straw are discarderdand specifically, it is estimated that in 2020, 74 million of wheat straw residueswill be available for advanced biofuels generatation.4 AD process has gained popularity in latter 20th century as a solution to energy and environmental concern and interestingly, co-digestion of different biomasses has gained attention in last few decades, especially in Denmark, Sweden and Germany, where it is conducted with imported cellulosic waste.5,6 Anaerobic co-digestion is an approach to increase the biogas production of feedstocks with low methane potential e.g. livestock manure,7 by the addition of substrates with higher methane potential,8 resulting in better overall plant economy.9 The benefits of codigestion were first reported in 1981 and it was found that manure gives a buffering capacity to the AD process along with improved nutrient balance, lower risk of ammonia inhibition and adjustment of C/N ratio.10 Moreover, the combination of abundant agricultural residues and biomass from non-arable land having no competition with the food chain, is considered ideal for anaerobic co-digestion due to the potential of achieving relatively higher methane productivity.11 For instance, in a study conducted by Somyaji and Khanna, 40% of the wheat straw with 60% of cattle manure on total solids (TS) basis showed an improved methane yield of 194 mLCH4/gTS compared to 174 mLCH4/gTS for cattle manure.12 Likewise in another study, it was reported that the 30% addition of oat straw to cow manure on VS basis increased 16% the volumetric methane production than cow manure mono-digestion at lab scale batch reactors.13 Co-digestion can be applied as means for improving the low biodegradability of e.g. lignocellulosic materials (complex structure of biomass and presence of lignin) or overcoming inhibition problems of e.g. manures (low biogas potential and ammonia inhibition). Moreover, a more balanced AD can be achieved as by adding lignocellulosic biomass with lesser nitrogen content, a stable pH can be maintained due to ammonia buffering in a manure-baseddigester.14
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Thus, the blend of substrates with dissimilar chemical composition can lead to a more effective digestion. For example, it has been previously suggested that grass silage could be a potential cosubstrate with livestock manures to significantly augment the methane production.15 But one of the biggest challenges for AD process is the complex structure of biomass and the presence of lignin that also adversely affects the process effectiveness.16 It is well established that content of specific macro and micro-nutrients is a key factor for successful digestion. For instance, nitrogen (N), sulphur (S), magnesium (Mg), sodium (Na), calcium (Ca) and iron (Fe) are considered as crucial nutrients for microbial growth.17 The micro-nutrients or trace metals e.g. chromium (Cr), cobalt (Co), copper (Cu), manganese (Mn), molybdenum (Mo), nickel (Ni), selenium (Se), vanadium (V) and zinc (Zn) mostly increase the efficiency of enzymes by attachment to their active sites.18 Generally, co-digestion performance is optimized by using different combinations and types of substrates, so that the bacterial community is provided with the suitable concentrations of carbon, nitrogen and micro, macro nutrients.19Another benefit of co-digestion is to overcome the volatile fatty acids (VFAs) and sulfide accumulation resulting in shortening of lag phase and increased rate ofbiomethanation.20 The aim of present study was to examine different co-digestion scenarios of wheat straw (WS) and meadow grass (MG) with cattle manure (CM), focusing on some macro and micro nutrients and C/N ratios that can promote a possible synergism for AD process and increase the rate of methane production to attain higher biodegradability values than mono-digestion. In addition, the modified Gompertz equation was used to analyze the process kinetics of the different codigestion scenarios.
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MATERIALS AND METHODS Collection of substrates Wheat straw (WS) was harvested from Zealand, Denmark and meadow grass (MG) was harvested from a field located in Lintrup (South Jutland, Denmark). Before usage, a size reduction step was conducted in order to improve the experimental accuracy.
Thus, the
lignocellulosic substrates were cut in size less than 0.5 cm using a cutting mill (SM 200, Retsch GmbH, Germany). Cattle manure (CM) was obtained from local farm in Denmark and was stored at 4 °C prior to use. The inoculum was obtained from Snertinge biogas plant Denmark and prior to usage was kept in a thermophilic incubator at (53 °C) to reduce its residual biogas production. Substrate and inoculum characterization The chemical composition of the inoculum, cattle manure (CM) and the lignocellulosic substrates are presented in Table1 and 2, respectively. Analysis in Table 3 is also presented for the metal ions found in substrates. All analyses were performed in triplicates and average values are presented in the tables with standard deviation. Analytical methods Standard protocols of APHA were employed to calculate, Total solids (TS), Volatile solids (VS), pH, total Kjeldahl nitrogen (TKN) and ammonium nitrogen (NH4-N).25 The pH of inoculum and cattle manure was measured by a PHM 92 LAB pH-meter. Volatile fatty acids (VFA) composition of manure and inoculum were measured according to Kougias et al.26 Specifically, VFA measurement was conducted by addition of 0.1 mL of 34% H3PO4 to 1.5 mL sample in 2 mL Eppendorf tube. The samples were centrifuged at 13,000 rpm for 12 min and supernatant liquid (1 mL) was placed by a pipette into GC vials filled with 100 µL internal standard (4-
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methyl-valeric acid) for GC analysis. Gas chromatograph (Shimadzu GC-8A, Tokyo, Japan) equipped with a glass column (2 m, 5 mm outer diameter, and 2.6 mm inner diameter) packed with Porapak Q 80/100 mesh (Supelco, Bellefonte, PA) and a flame ionization detector (FID) was used to determine the methane contents of the batch assays. The injection and detection temperatures were 110 and 160 °C, respectively. Strong acid hydrolysis protocol from National Renewable Energy Laboratory (NREL) was used to determine structural carbohydrates and Klason lignin.19 Hewlett-Packard Agilent 1100 chromatographer with a BioRad- Aminex HPX78H column (dimensions of 300.0 × 7.8 mm) at pH 3.0 with 4 mM H2SO4 as an eluent, at a flow rate of 0.6 mL/min was used to determine sugar contents. The trace metals analysis was performed with digestion of lignocellulosic residues using HNO3 and HCl followed by analysis using VARIAN Inductive Coupled Plasma optical emission spectrophotometer (ICP-OES). An elemental analyzer (vario MACRO cube, Hanau, Germany) was used to determine CHNOS and analyze the C/N ratio. All determinations were performed in triplicates. BMP assay Thermophilic (53°C) batch experiments were performed according to the biochemical methane potential (BMP) protocol defined by Angelidaki et al.27 The batch reactors had total volume of 547 mL and working volume of 200 mL. The inoculum accounted for 40% of the working volume and the initial organic load was set to 2 gVS/L. Cattle manure, wheat straw and meadow grass were digested separately to determine their methane yield and also in different combining ratios to elucidate the effect of co-digestion process. For all co-digestion combinations, one of the three substrates was kept constant at three different levels (i.e. 25%, 50% and 75% of total initial VS load) and the left over portion of initial VS contents was distributed between the
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remaining two substrates as 25:75, 50:50, and 75:25 for each constant level of the first substrate (Table 4). The batch reactors were shaken once every day in order to avoid the creation of dead zones in the reaction mixture. Avicel® PH-101 cellulose (Sigma Aldrich) was used to validate the accuracy of the BMP assay process. Batch reactors only with inoculum and water (blanks) were included to determine the residual methane production from the inoculum. Finally, the batch reactors were flushed with a N2/CO2 (80/20% v/v) gas mixture, closed with rubber stoppers and aluminum caps, and incubated at 53 °C. All BMP experiments were performed at least in triplicates.
Theoretical biomethane potential, synergistic effect and biodegradability calculation Theoretical biomethane potential was calculated from Buswell’s formula28 and extent of biodegradability was calculated by the following equation: Pex BD % = × 100 Pth
(1)
Pex is experimental biomethane yield and Pth is the theoretical biomethane yield The synergistic effect (η) was calculated by the following equation. A η value, greater than one indicated synergistic effect and less than one antagonistic effect.
η=
Exp.Methane Pred .Methane
(2)
Elemental analysis was only confined to organic matter and the distribution of elements was calculated on the basis of VS. Furthermore, final concentrations of trace elements in the monodigestion were calculated by the following equation, ConcentrationX ( mg / L ) = ( mgX / kgVS ) X (VS load )
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(3)
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Where X is the element for which the calculation is done and VSload is the final VS load in the reactor. For each co-digestion the final elemental concentration was calculated by the addition of each element in mono-digestion multiplied by its percentage VSshare in total VS. C final = ( CWS × VS share ) + ( CMG × VS share ) + ( CCM × VS share )
(4)
C is the concentration of metal ion in mono-digestion and is multiplied with its VSshare in every co-digestion scenario. Cfinal is the final concentration (mg/L) of specific metal ion in co-digestion mixture. Kinetic analysis The kinetic analysis provides information on the extent of biodegradability and the rate of biodegradability of a particular substrate and/or combination of them. The modified Gompertz equation29 was used to determine the kinetic parameters that describe the degradation process of organic matter in batch assay:
Rmax × e M = P × exp − exp × ( λ − t ) + 1 P
(5)
Where M is the methane yield (NmLCH4/gVS) at time t (days), P is the maximum methane potential (NmLCH4/gVS), Rmax is the maximum methane production rate (NmLCH4/gVS/d), e is the Euler’s constant and λ is lag phase (days). The parameter estimation was performed using the solver tool of Microsoft excel program. Statistical analysis Graphpad Prism was used to perform the comparison among the experimental data (Graphpad Software version 5, Inc., San Diego, California). Descriptive statistics were conducted for all data and mean values and standard deviations were calculated. Comparisons of the means between the different groups were conducted by using one-way analysis of variance (ANOVA)
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and significant differences (p < 0.05) among the achieved methane yields were identified using Tukey Post-Hoc Analysis.
RESULTS AND DISCUSSION BMP batch results Wheat straw mono- and co-digestion (BMP SET 1) The anaerobic co-digestion of lignocellulosic substrates with cattle manure was examined during the present study, for identifying the most promising combinations that can enhance the methane yield. In mono-digestion experiments, the ultimate methane yields were determined to be 302±14 NmLCH4/gVS for CM; 307±18 NmLCH4/gVS for MG; and 255±17 NmLCH4/gVS for WS. The achieved methane yields are in accordance with literature values for MG, 282-340 NmLCH4/gVS30; CM, 324 NmLCH4/gVS30; and WS, 254 NmLCH4/gVS.31 The lower methane yield of CM in the study compared to literature is explained by the fact that the CM was not sieved and contained hardly degradable lignocellulosic fibers. Along with mono-digestion, different combinations of co-digestion were investigated (Table 4). In the first set of BMPs, the combinations where half of the VS originated from WS and rest was distributed among CM and MG (i.e.WS50A:25/75, WS50B:50/50, WS50C:75/25) showed the maximum increase in methane yield. More specifically, the maximum experimental methane yield was achieved for the combination WS50B (316±4 NmLCH4/gVS), which was 24% significantly higher (p < 0.05) compared to WS mono-digestion. The alternative combinations WS50A and WS50C also exhibited a significant enhancement of methane yield by 20% (307±9 NmLCH4/gVS) and 22% (310±18 NmLCH4/gVS) compared to WS mono-digestion (p < 0.05). Previously, it was also found that 40:60 combination of wheat straw and cattle manure on organic matter basis was most promising for optimum biogas production.32 Moreover, the
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combinations with 25% and 75% also showed significant increase of 17% and 13%, respectively (p < 0.05). On the other hand, rest of the combinations in this BMP set did not show any significant enhancement (p > 0.05) over WS mono-digestion. So, here in co-digestion scenarios where half of the total VS was provided by WS (i.e. WS50 A, B and C) plus the combinations WS25C and WS75C showed a synergistic effect (η > 1) (Table 4). Usually 15:1 to 45:1 C/N ratio is considered optimal for AD process33 but the mono-digestion here contained C/N ratio of 103 due to very low nitrogen in WS. This value was corrected in co-digestion scenarios by the addition of CM and MG with much lower C/N ratios of 16 and 19, respectively. Furthermore, the selected nutrient metal concentrations in the co-digestion scenarios were also found higher in all co-digestion scenarios of BMP set 1. Specifically, Ca, Fe, Mg, Na and Ni were higher for codigestion than mono-digestion. Although, the differences of nutrient metals between mono- and co-digestion are very small (Table 5) these small variations can lead to significant improvements in AD performance.34 For instance, in previous study increasing Ni concentration from 1 mg/L to 2 mg/L by adding NiCl2·6H2O increased the methane production by 20%.35 Ni increases the activity of Ni dependent metalo-enzymes for biogas production.36 So, it can be hypothesized that the improved C/N ratios and increase in specific nutrient ions as Ni, played a synergistic role to increase the biomethanation process in co-digestion and enhanced methane yield as compared to mono-digestion. Meadow grass mono- and co-digestion (BMP SET 2) In BMP set 2, the combinations MG25 A, B and C decreased the methane yield compared to grass mono-digestion, due to the lower fraction of easily biodegradable substrate (i.e. MG) and higher amount of recalcitrant fraction (i.e. WS). In set 2, the highest methane yield (351±25 NmLCH4/gVS) was observed for MG75A and it was found to be 14% significantly higher (p
0.05). The combinations with 75% of CM (i.e. CM75A, B, C) also presented the highest η values (1.22, 1.21 and 1.25, respectively), indicating that the increase in methane production was not only additive but synergistic. Rest of the combinations in BMP set 3 also showed synergistic effect (η > 1) but with lower values than CM75 A, B, and C. The concentration of nutrient metals in all co-digestion scenarios of BMP set 3were determined to be markedly lower compared to CM mono-digestion due to reduction in CM share compared to 100% in mono-digestion. So, decrease in CM share leads to decrease in nutrient metal ions. CM usually has very low VS content37 so, addition of lignocellulosic biomass was required to increase organic matter contents of co-digestion mixture. Moreover, in BMP set 3 the addition of lignocellulosic biomass increased carbon source hence varied the C/N ratio. So, increase in the carbon content of codigestion mixture can increase the methane yield significantly over CM that has high nitrogen instead of carbon. Therefore, the highest enhancement in methane yield and biodegradability were observed in CM75C, which contained also fewer amounts of recalcitrant WS. Moreover clear synergistic effect, relative to mono-digestion was observed for this do-digestion combination.
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Kinetic analysis The differences among the kinetic parameters (i.e. methane production rates, estimated methane potential and lag phase) were also analyzed. All of the above mentioned parameters were estimated using modified Gompertz equation that describes bacterial growth.39 The estimated parameters are also presented in Table 6. In the first set of BMPs, the Rmax values for WS50 A, B and C were found to be approximately 50%, 28% and 22% higher than the WS alone, while the other combinations with 25% and 75% WS did not show elevated Rmax values than WS50 A, B and C. Moreover, for these combinations of 50% WS share the lag phase values were 10, 9 and 9 days respectively, which are lower than the value of 12 days for WS mono-digestion. Krishania et al. also reported a lag phase of 16.73 days for WS mono-digestion32 that is higher than found in this study, probably due to difference in temperature conditions; our study was conducted at thermophilic conditions. The increase in Rmax can be explained by the increased estimation of Zn, Fe and Ni in WS50 A, B and C compared to mono-digestion of WS. The aforementioned metal ions are co-factors for enzymes needed for the overall anaerobic digestion process.40,41 So the enrichment of these ions was achieved by improving feedstock composition through co-digestion.42 Regarding the BMP set 2, MG75A was the most promising combination associated with 25% higher methane production rate compared to mono-digestion. Moreover, MG75B and C also showed 15% and 20% enhancement in Rmax. Increase in MG share was also found associated with enhanced methane production rate from 15 mLCH4/gVS/d (MG25C) to 25 mLCH4/gVS/d (MG75A). It was previously found that increase in MG (i.e. 12, 23 and 34 g/L) and CM codigestion enhances the methane production rate by 25, 63 and 114% compared to CM.43 Lag
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phase in this co-digestion setup remained constant due to higher lignocellulosic share of WS or MG in all combinations. Concerning the third BMP set, the combinations with 75% VS share from CM did not show an increase in Rmax. On the other hand the combinations with 25% CM share showed 4%, 13% and 22% increase in Rmax as compared to CM mono-digestion. Usually, cattle manure alone is not considered good for because it contains already digested organic matter that has low potential of methane production.41 So, increase CM share increases already degraded organic content addition of some high energy organic content. Therefore, it is needed that some high energy content should be added to increase the theoretical methane yield of system (i.e. MG and WS). Finally decrease in lag phase was observed to be associated with decrease in lignocellulosic biomass and increase in CM share. This observation is in agreement with study that concluded lignocellulosic substrates need a longer digestion time for degradation due to the complex structure of lignocellulosic polymer.44,45
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CONCLUSIONS In present study the co-digestion scenarios showed improved biodegradability and significantly enhanced methane yield as compared to respective mono-digestion. Co-digestion of two lignocellulosic residues of markedly different C/N ratio and lignin contents with CM improved the biodegradability up to 84%. Moreover, increase of WS and MG share and decreased CM in co-digestion were found to be coupled with prolonged lag phase. Furthermore, the higher methane production rates were found associated with increase in MG share. Furthermore, it was concluded that co-digestion of two lignocellulosic substrates of different physicochemical characteristics with CM offered increase in biodegradability due to optimum conditions. Finally, WS provided carbon source and mainly adjusted the C/N ratios of co-digestion scenarios studied and MG share added the ease of biodegradability.
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TABLES. Table 1. Chemical characterization of inoculum and cattle manure. Parameters
Inoculum
Cattle manure (CM)
Total solids (TS) (g/kg)
27.5±0.0
35.4±0.1
Volatile solids (VS) (g/kg)
1.7±0.0
24.9±0.1
Total Kjeldahl nitrogen (TKN) (g/kg)
3.6±0.1
2.6 ±0.10
Ammonium nitrogen (NH4-N) (g/kg)
3.5±0.1
1.7±0.05
pH
8.03
6.90
Total volatile fatty acids (VFA) (mg/L)
202.2±15.2
7031.0±25.0
Acetate (mg/L)
144.3±12.3
4486.0±21.5
Propionate (mg/L)
38.5±2.1
1427.0±25.7
Isobutyrate(mg/L)
5.0±0.2
144.0±13.1
Butyrate (mg/L)
0.9±0.1
711.0±24.9
Isovalerate (mg/L)
5.1±0.3
205.0±12.1
Valerate (mg/L)
0.0±0.0
41.0±2.2
n-hexanoate (mg/L)
1.4±0.8
12±1.1
C/N Ratio
-
16
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Table 2. Chemical characterization of lignocellulosic substrates. Parameters
Wheat straw (WS)
Meadow grass (MG)
TS (% w/w)
92.8±0.1
93.4 ±0.2
VS (% w/w)
86.7±0.4
89.6±0.6
Cellulose (% TS)
42.0 ±0.7
39.2±8.2
Hemicellulose (% TS)
30.8 ±0.5
19.8±0.0
Klason lignin (% TS)
26.7±2.7
14.7±0.5
TKN (g/kg)
4.8±0.1
19.3 ±0.0
NH4-N (g/kg)
0.8 ±0.1
2.9±0.2
C/N ratio
103±4.8
19±0.3
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Table 3. Analysis of selected metal ions for substrates used (mg/KgVS). Metal Ions
Wheat Straw
Meadow Grass
Cattle Manure
Optimum For AD (mg/L)
WS±SD
MG±SD
CM ± SD
Ca
3308±94
6660±321
4651±358
>0.54-4021
Fe
41±2.3
5±1
2374±15
1-1022
Mg
1184±7
1750±51
1240±135
75-15023
Na
156±12
636±24
6302±135
100–20023
Ni
1±0
1±0
275±45
0.0059-521
K
9258±237
11903±1408
8013±429
< 40024
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BMP SET 1
Table 4. Organic matter distribution and aggregated results of BMP assays. Sample name
WS100
WS25A
WS25B
WS25C
WS50A
WS50B
WS50C
WS75A
WS75B
WS75C
Cattle Manure**
0
25
50
75
25
50
75
25
50
75
Meadow Grass**
0
75
50
25
75
50
25
75
50
25
Wheat Straw*
100
25
25
25
50
50
50
75
75
75
C/N ratio
103
39
39
38
61
60
60
82
82
81
Pth (NmLCH4/gVS)
443
442
435
428
433
438
442
438
440
442
BD (%)
58
61
61
70
71
72
70
60
62
65
293±17
292±16
291±16
281±17
280±17
279±16
268±17
268±17
267±17
272±10
267±14
298±21
307±9
316±4
310±18
264±2
275±11
288±23
Increase %
7
5
17
20
24
22
3
8
13
Significance
ns
ns
b
b
b
b
ns
ns
b
Synergistic effect (η)
0.93
0.91
1.03
1.09
1.13
1.11
0.98
1.03
1.08
PPred (NmLCH4/gVS ± SD) PEx (NmLCH4/gVS ± SD)
BMP SET 2
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
Energy & Fuels
255±17
Sample name
MG100 MG25A MG25B MG25C
MG50A MG50B MG50C MG75A MG75B MG75C
Cattle Manure**
0
25
50
75
25
50
75
25
50
75
Meadow Grass*
100
25
25
25
50
50
50
75
75
75
ACS Paragon Plus Environment
Energy & Fuels
Wheat Straw**
0
75
50
25
75
50
25
75
50
25
C/N ratio
19
66
49
33
50
39
28
34
29
23
Pth (NmLCH4/gVS)
414
441
439
437
430
431
432
422
422
423
BD (%)
74
61
62
66
67
73
74
83
79
81
277±17
286±16
294±16
287±17
293±17
299±17
297±18
300±18
303±17
268±6
273±14
286.9±11 288±15
315±28
319±27
351±25
332±26
343±13
Increase %
-13
-11
-7
-6
3
4
14
8
12
Significance
a
ns
ns
ns
ns
ns
a
ns
ns
Synergistic effect (η)
0.97
0.95
0.98
1.00
1.08
1.07
1.18
1.10
1.13
PPred (NmLCH4/gVS ± SD) PEx (NmLCH4/gVS ± SD)
BMP SET 3
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
Page 20 of 31
307±18
Sample name
CM100 CM25A CM25B CM25C
CM50A CM50B CM50C CM75A CM75B CM75C
Cattle Manure*
100
25
25
25
50
50
50
75
75
75
Meadow Grass**
0
25
50
75
25
50
75
25
50
75
Wheat Straw**
0
75
50
25
75
50
25
75
50
25
C/N ratio
16
65
50
34
49
39
28
33
27
22
Pth (NmLCH4/gVS)
452
429
434
440
444
440
437
448
446
444
BD (%)
67
71
72
74
72
76
76
80
80
84
ACS Paragon Plus Environment
Page 21 of 31
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
Energy & Fuels
PPred (NmLCH4/gVS ± SD)
277±17
286±17
296±17
285±16
291±16
298±16
293±15
296±15
300±15
305±16
314±17
324±21
322±25
333±29
330±16
358±25
358±15
375±21
Increase %
1
4
7
7
10
9
19
19
25
Significance
ns
ns
ns
ns
ns
ns
a
b
b
Synergistic effect (η)
1.10
1.10
1.10
1.13
1.14
1.11
1.22
1.21
1.25
PEx (NmLCH4/gVS ± SD)
302±14
*represents the percentage of VSshare out of total VS load (presented in bold numbers), ** represents the percentage of rest of VS share (TVS– 100) (TVS= Total VSshare), Significance: a = p < 0.05 , b = p < 0.05
ACS Paragon Plus Environment
Energy & Fuels
BMP SET 1
Table 5. Final Concentrations (mg/L) of trace metals in each co-digestion scenario.
BMP SET 2
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
Page 22 of 31
WS100
WS25A
WS25B
WS25C
WS50A
WS50B
WS50C
WS75A
WS75B
WS75C
Ca
7±0
11±1
10±1
9±1
9±0
9±1
8±1
8±0
8±0
8±0
Fe
< 0±0
1±0
2±0
3±0
1±0
1±0
2±0
< 0±0
1±0
1±0
Mg
2±0
3±0
3±0
3±0
3±0
3±0
3±0
3±0
3±0
3±0
Na
< 0±0
3±0
5±1
7±1
2±0
4±0
5±1
1±0
2±0
3±0
Ni
< 0±0
1±0
2±0
3±0
1±0
1±0
2±0
