Effect of chemical structure of lignite and high-volatile bituminous coal on the generation of biogenic coalbed methane

Fuel 245 (2019) 212–225

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Full Length Article

Effect of chemical structure of lignite and high-volatile bituminous coal on the generation of biogenic coalbed methane Shao Pei, Wang Aikuan, Wang Wenfeng

T

⁎

Key Laboratory of Coalbed Methane Resources & Reservoir Formation Process, Ministry of Education, China University of Mining & Technology, Xuzhou 221008, China School of Resources and Geosciences, China University of Mining & Technology, Xuzhou 221116, China

ARTICLE INFO

ABSTRACT

Keywords: Biogenic coalbed gas Experimental simulation Chloroform asphalt “A” Chemical structure Lignite Bituminous coal

Biogenic coalbed methane has been attracted much attention due to massive reserves and green performance, but the current research is relatively weak. To further investigate its formation mechanism, the experimental simulation of biogas generation was performed by using lignite, high-volatile bituminous coals and their treated coals as substrates for 90 days. The results show that the lignite has a greater biogas potential than high-volatile bituminous coal in this study. Total gas production in lignite groups (L-BZ-1 and L-LJ-1) is 12.6% more than the bituminous coal groups in the experimental simulation. This is because the lignite has a low degree of thermal evolution and rich in soluble organic matter: chloroform asphalt “A” (CAA), which plays an important role in microbial metabolism to produce biogas. The CAA in coal has a conversion rate of 3.08 mL/g into biogas in this experimental simulation. The saturated hydrocarbons and nonhydrocarbons are more biodegradable components in the CAA. In saturated hydrocarbons, the n-alkanes with shorter chains or an odd carbon number are preferentially degraded. In the experimental simulation, biogas generation results in the consumption of a large number of organic matters with heteroatomic groups such as hydroxyl, carboxyl, pyridine and nitrogen oxides. Aliphatics show a stronger bioactivity than aromatics. The aromatic structure in coal is a few biodegraded in the later stage.

1. Introduction Coal is the world’s largest and most widely distributed conventional energy. However, it is mainly categorized as low-ranked lignite and subbituminous coals [1], which have low commercial and heating values [2]. Moreover, the traditional way of coal combustion caused the release of toxic and harmful substances, which brought great negative impact on human habitat [3]. Fortunately, the presence of biogenic coalbed gas has been reported in coal reserves in many countries (Table 1). This inspires an efficient and environmentally-friendly means: biological conversion of coal to methane. At present, four methods are mainly used for enhancing biological conversion of coal to methane: 1) microbial stimulation [4–7]; 2) microbial augmentation [1,8–10]; 3) creation of a more suitable environment for the microorganisms (e.g., the adjustment of temperature, pH, and NaCl concentration [11]); 4) increase in the bioavailability of coal organics [12–16]. However, a key knowledge gap must be addressed before these methods can be implemented on a large scale. What fraction of coal is biodegradable? The bioconversion of coal-to-methane involves a multi-stage process

⁎

that can be completed by a variety of microorganisms together [7,26]. Coal is biodegraded by hydrolytic and fermentative bacteria into substrates (e.g., carbon dioxide, hydrogen and acetate) that can be utilized by methanogens to initiate methanogenesis, which results in the production of methane [27,28]. It can be found that the biogenic coal-tomethane conversion largely depends on the presence of some organic components. However, the organic matter of which chemical structure in coal has not yet been defined. Experimental simulation of biogenic coalbed gas has been attracted much concern to better understand the formation mechanism [29–35]. Although the bioconversion of coal-to-methane may be constrained by multiple factors, the biogas production will ultimately depend on content of the bioavailable substrates [29,31,36]. A large number of experiments have shown that biogas yield is closely related to the bioavailable organic materials present in coal, including volatile fatty acids and compounds with numerous oxygen-containing functional groups [26,29,32,37]. Accordingly, the previous studies have indicated that biogenic methane generation from coal can be stimulated by supplying an external substrate [9,38]. These findings have laid the foundation for exploring coal bioavailability using geochemical assays. However, it

Corresponding author at: No.1, Daxue Road, Xuzhou, Jiangsu, China. E-mail address: [email protected] (W. Wang).

https://doi.org/10.1016/j.fuel.2019.02.061 Received 19 November 2018; Received in revised form 4 February 2019; Accepted 13 February 2019 Available online 20 February 2019 0016-2361/ © 2019 Elsevier Ltd. All rights reserved.

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Table 1 Biogenic gas reserves in coal-bearing basins in different zones. Location

Coal rank

CH4 (%)

Gas origin

Springfield, Indiana, USA South-central Wyoming, USA Powder River Basin, USA San Juan Basin, USA Sydney and Bowen Basins, Australia Ruhr Basin, Germany Huntly Coalfield, New Zealand Huainan Coalfield, China Qaidam Basin, China

High volatile bituminous Subbituminous, high-volatile bituminous Subbituminous Subbituminous, low-volatile bituminous High-volatile bituminous Anthracite Subbituminous C to A High-volatile bituminous Lignite

> 99 97 97 81–96 > 95 1–95 > 90 > 99 > 98

Biogenic Thermogenic Biogenic Thermogenic Thermogenic Thermogenic Biogenic Thermogenic Biogenic

has been rarely studied that which functional groups play a role in biogas generation for different ranks of coals. In this paper, experimental simulation of biogenic coalbed gas generation was performed by using lignite, high-volatile bituminous coals and their treated coals as substrates. The correlation between biogas production and soluble organic matter in coal was investigated to study influence mechanisms of coal material for biogas generation. The changes in chemical structure of coals were studied by comparing FT-IR, Raman and XPS analysis results of coal samples before and after the experimental simulation. The results will provide guidance for evaluating biogas potential of source rock and a supplement for understanding generation mechanism of biogenic coalbed gas.

Refs. and biogenic and biogenic and biogenic and biogenic and biogenic

[17] [18] [19] [20] [21] [22] [23] [24] [25]

ratio of the extract and the coal sample. The CAA is composed of saturated hydrocarbons, aromatic hydrocarbons, nonhydrocarbons and asphaltenes. Their separation was performed using a rod chromatography analyzer (model MK-6S) according to the Chinese petroleum industry standard protocol (SY/T 5119-2008). Thin layer chromatography with flame ionization detection (TLC/FID) was at a constant temperature of 15 °C. The fractionation of n-alkanes in saturated hydrocarbons was conducted using the Chinese petroleum industry standard protocol (SY/T 5779-2008). This process was completed using a gas chromatographic analyzer (model Agilent 7890 GC), which was equipped with an elastic quartz capillary column with an internal diameter of 0.25 mm and a length of 30 m. The detection temperature of the FID detector was 320 °C, and the temperature of the vaporization chamber was 310 °C. All powdered coals (- 200 mesh) were dried for 24 h at 60 °C in a vacuum drying oven. Raman experiments were performed at a laser confocal Raman spectrometer (Bruker Senterra) with an excitation wavelength of 532 nm. The spectral range is 45 cm−1 to 4500 cm−1 and spectral resolution is 0.5 cm−1. Fifteen milligrams dried sample was initially ground with 200 mg of KBr for 120 min in a grinding mill in a nitrogen atmosphere. The mixture was molded into a disc, which was measured using a VERTEX 80v Fourier transform infrared (FT-IR) instrument (Bruker Corporation, Karlsruhe, Germany). The spectra were recorded by collating 100 scans with wavenumbers ranging from 400 cm−1 to 4200 cm−1 at a resolution of 0.06 cm−1. XPS experiments were conducted by an X-ray photoelectron spectrometer (ESCALAB 250Xi, Thermo Fisher, America) with a monochromatic aluminum anode target. The spot size is 650 μm. The spectra of survey scan were record by the pass energy of 100 eV with a step size of 1.0 eV. The spectra of high resolution scan were obtained at the pass energy of 20 eV with a step size of 0.05 eV. All data was corrected based on C–C band with a binding energy of 284.8 eV. The spectra of high resolution scan were fitted using the software XPS peak fit 4.1.

2. Experiential materials and methods 2.1. Samples and testing In this study, lignite was collected in the Beizao and Liangjia mines in the Longkou coalfield, and bituminous coals were derived from the Panyi, Pansan, Xinji, and Zhangji mines in the Huainan coalfield, China. They were labeled L-BZ, L-LJ, B-PY, B-PS, B-XJ, and B-ZJ, respectively. The maximum vitrinite reflectance (Ro, max) of lignite and bituminous coals is about 0.4% and 1.0% (Table 2). The volatile matter contents in all samples are greater than 37%, ash yields are approximately 10%, and total sulfur contents are less than 1%. Compared to the bituminous coals, the lignite (L-BZ and L-LJ) has higher atomic hydrogen to carbon and atomic oxygen to carbon ratios. Mad: moisture on an air dried base; Ad: ash on a dry base; Vdaf: volatile matter on a dry and ash-free base; FCd: fixed carbon content on a dry base. Elements were determined on a dry and ash-free base, except for sulfur, which was on a dry base, and H/C and O/C are the atomic ratios of hydrogen to carbon and oxygen to carbon in elemental analyses. The CAA was extracted from the coal samples using a Soxhlet extractor according to the Chinese petroleum industry standard protocol (SY/T 5118-2008). Eight grams of sample (-200 mesh) and 330 mL of trichloromethane (AR) were placed into the extraction tube and the flask, respectively. The extraction process was conducted for 72 h at a constant temperature of 80 °C. After extraction, the leaching liquor was concentrated, filtered, and washed with trichloromethane 5 times. Finally, the filtrate was dried at a constant temperature of 60 °C in a vacuum drying oven until a constant weight was obtained. The extraction yield for the CAA can be obtained by determining the mass

2.2. Experimental simulation The mine water containing microbes was collected from the Dananhu mine, China. Microbial cultivation was performed in a serum bottle. A syringe (Vol. 50 mL) connected with a two-way valve, a threeway valve and a needle was used to collect generated gas at room temperature and one bar of pressure (Fig. 1). The collected gas was

Table 2 Elemental and proximate analyses of the coal samples (%) [39]. Coal

Ro,

L-BZ L-LJ B-PY B-PS B-XJ B-ZJ

0.39 0.42 1.02 1.07 0.96 0.99

max

Odaf

Cdaf

Hdaf

Ndaf

St,d

H/C

O/C

Mad

Ad

Vdaf

FCd

19.89 14.38 9.00 10.28 14.30 10.15

72.54 77.67 83.54 82.21 78.92 82.70

5.06 5.77 5.37 5.23 4.93 5.36

1.63 1.70 1.66 1.65 1.57 1.58

0.53 0.43 0.36 0.57 0.24 0.18

0.84 0.89 0.77 0.76 0.75 0.78

0.21 0.14 0.08 0.09 0.14 0.09

7.54 7.32 1.24 1.54 1.88 1.68

9.69 9.82 12.94 10.48 12.19 11.23

43.08 45.17 38.07 38.37 42.28 37.81

39.79 37.69 53.92 55.17 50.68 55.21

213

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Fig. 1. Schematic diagram of experimental simulation.

determined by the East and West Electronic chromatograph (model GC4000A). These processes of enrichment culture and gas chromatography have been illustrated in detailed in a previous report [39]. The experimental simulation for biogas generation were performed on eleven groups, including one control group (KB), six raw coal groups (L-BZ-1, L-LJ-1, B-PY-1, B-PS-1, B-XJ-1, and B-ZJ-1), and four treated coal groups (L-BZ-2, L-LJ-2, B-PY-2, and B-XJ-2). The solution in all serum bottles is made up of 50 mL of enrichment culture solution and 380 mL of culture medium. With the exception of the control group, 24 g of coal samples were added to each group. In the treated coal group, the substrate was coal samples extracted using trichloromethane. The experimental simulation was carried out for 90 days, and the headspace gas was periodically collected during the incubation period (at 10, 20, 30, 40, 50, 70, and 90 days).

Table 3 Extraction yield of CAA and its components.

3. Results

dominated by long-chain n-alkanes (n-C21-/n-C22+; 0.21–0.44) (Table 4, Fig. 2). This suggested that organic matter is mainly originated from terrestrial higher plants during coal-forming period [46]. Compared with bituminous coal samples, the lignite samples have a greater carbon preference index (CPI) that was greater than 2 on average, which may be related to their lower thermal maturity [47]. Pristane (Pr) and phytane (Ph) are common acyclic isoprenoids that are widely distributed in nature, and their ratio (Pr/Ph) can be an indicator to determine the coalforming plants and sedimentary environment [48,49]. The Pr/Ph ratio of the bituminous coals is above 3 (with the exception of B-PY), which may indicate a normal level of thermal evolution in the bituminous coals (Ro, max: 0.96–1.07). The organic matter in two lignite samples show a predominant pristine content (Pr/Ph = 6.8 and 7.3), which may be attributed to an input of terrestrial higher plants during coal-forming period [49]. The Pr/n-C17 ratio of six samples ranged from 2.42 to 4.50 (average 3.23), and the Ph/n-C18 ratio was in the range of 0.40–0.89. The ratio of Pr/n-C17 versus Ph/n-C18 in the six samples was in the range of 3.92–10.22, with an average of 5.57. These suggest that the coals were formed at a weak oxidizing environment [50,51].

Samples

L-BZ L-LJ B-PY B-PS B-XJ B-ZJ

Extraction yield (%)

2.50 2.68 2.04 2.13 2.20 2.31

Components (%) SH

AH

NH

AS

15.14 11.40 1.98 1.91 2.58 2.41

20.44 20.57 14.58 15.19 25.66 17.74

42.67 48.89 31.05 30.68 31.45 31.77

21.76 19.14 52.38 52.23 40.32 48.09

SH/AH

TH (%)

0.74 0.55 0.14 0.13 0.10 0.14

35.58 31.97 16.56 17.1 28.24 20.15

SH–Saturated hydrocarbons; AH–Aromatic hydrocarbons; NH–Nonhydrocarbons; AS–Asphaltenes; OH–Total hydrocarbons, is summary of SH and AH.

3.1. Organic geochemistry The extraction yield of CAA can be used as a significant indicator to evaluate the hydrocarbon generating potential of organic matter [40]. The extraction yields of CAA in the six samples exceed 2% (Table 3) and are greater than the abundances of soluble organic matter in source rock in previous reports [41–44]. Based on the evaluation standards used to determine the hydrocarbon generation potential of coal source rock [45], these samples can be classified as very good source rock. However, the components of the CAA in lignite are different from those in high-volatile bituminous coals. The proportions of saturated hydrocarbons, aromatic hydrocarbons, and nonhydrocarbons in lignite are greater than 10%, 20%, and 40%, respectively, and are significantly higher than those in bituminous coals. This suggests that lignite has a greater potential for biogas generation. In the gas chromatograms, n-alkane distribution shows a unimodal pattern with a maximum peak (n-C25, n-C27, or n-C29), and it is 214

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Table 4 Relative parameters of n-alkanes and isoprenoid alkanes in the samples. Samples

Max-Peak

n-C21−/n-C22+

(n-C21 + n-C22)/(n-C28 + n-C29)

CPI

Pr/Ph

Pr/n-C17

Ph/n-C18

L-BZ L-LJ B-PY B-PS B-XJ B-ZJ

C27 C29 C25 C25 C27 C27

0.30 0.29 0.40 0.44 0.21 0.29

0.94 0.69 9.29 2.34 1.00 1.28

1.98 2.43 1.32 0.94 1.26 1.05

7.30 6.80 1.46 3.29 3.53 3.71

2.42 4.50 2.67 2.47 3.39 3.96

0.40 0.44 0.68 0.61 0.72 0.89

CPI =

1 2

(C25 (C24

C33)odd C32)even

+

(C25 (C26

C33)odd C34)even

.

Fig. 2. Gas chromatograms of saturated hydrocarbons in the samples.

3.2. Amount and components of biogas

Table 5 Amount of collected headspace gas in different time periods (mL).

The accumulation of headspace gas in the KB was 279.8 mL (Table 5), which indicated that medium can provide the energy and carbon source needed by microbes to produce biogas. Over 90 days, the accumulation of headspace gas in lignite groups (L-BZ-1 and L-LJ-1) is 510.6 mL and 518.3 mL with an average of 514.45 mL. Total amount of four bituminous coal groups ranges from 429.1 mL to 494.2 mL (on average 456.83 mL). Compared to the raw coal groups, the four treated groups showed a significant reduction in gas production in 90 days. Their average accumulation is 307.33 mL, which is 175.9 mL less than the corresponding raw coal groups on average. This means that CAA in coal can be transformed into biogenic gas by microbes in this experimental simulation (a conversion rate of 3.08 mL/g on average, based on the Eq. (1)). It suggested that the CAA in coals plays an important role in biogas generation. The headspace gas is mainly composed of CH4 and CO2. With

Samples

KB L-BZ-1 L-LJ-1 B-PY-1 B-PS-1 B-XJ-1 B-ZJ-1 L-BZ-2 L-LJ-2 B-PY-2 B-XJ-2

215

Days 10

20

30

40

50

70

90

Total

6.7 14.2 13.8 58.7 48.2 55.4 94.7 5.3 9.8 10.3 8.9

28.2 26.3 23.1 258 264.2 278.9 268.1 21.2 18.5 32.3 35.4

215 324.1 342.4 39 31.1 29.7 18.8 189.2 204.6 177.1 190.3

23.2 62.3 57.2 28.6 25.2 29.4 31.8 51.4 45.3 40.2 61.2

6.7 18.5 17.3 25.3 13.1 11.6 30.8 17.2 15.4 12.3 15.3

0 16.9 17.3 13.9 17.9 17.9 18.3 13.6 10.7 8.5 9.1

0 48.3 47.2 30.5 29.4 27.1 31.7 9.9 7.2 3.4 5.7

279.8 510.6 518.3 454 429.1 450 494.2 307.8 311.5 284.1 325.9

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(a)

100

Relative content of CO 2 (%)

Relative content of CH 4 (%)

Fig. 3. Percentage of gas components in headspace gas.

80 60 B-PY-1 B-PS-1 B-XJ-1 B-ZJ-1

KB L-BZ-1 L-LJ-1

40 20 0 10

20

30

40

50

60

70

80

90

(b)

100 80

B-PY-1 B-PS-1 B-XJ-1 B-ZJ-1

KB L-BZ-1 L-LJ-1

60 40 20 0 10

20

30

40

Time (d)

50

60

70

80

90

Time (d)

Fig. 4. Change of (a) CH4 content and (b) CO2 content [39].

exception of them, heavy hydrocarbons, such as C2H6, C3H4, and nC4H10 were detected in the control and bituminous coal groups (Fig. 3). Changes of CH4 content can be described in terms of three stages: the ascending, descending, and ascending stage. However, changes of CO2 content show a descend-ascend-descend trend (Fig. 4). This pattern of reverse variation between the two indicated that CH4 production was partially caused by CO2 consumption via CO2-utilizing methanogens. In the bituminous coal groups, the generation of heavy hydrocarbons, which was rarely reported before, may be attributed to transition metal elements motivating acetoclastic methanogens to degrade aliphatic acids with low molecular weight, which has been discussed in a previous report [39].

T Ti2 CBi = i1 EYi × 24

chemical structure change resulting from microbial degradation can be characterized by four Raman parameters: full wave at half maximum (FWHM-D1 and FWHM-G), peak separation P(G-D1) and peak intensity ratio ID1/IG. Average values of FWHM-D1, FWHM-G and ID1/IG of the bituminous coals (B-PY-1 and B-XJ-1) are 185.5, 106.5 and 1.22, respectively, which are all lower than them of the lignite (L-BZ-1 and LLJ-1). However, Average value (233.86) of P(G-D1) of the bituminous coals is higher than it (231.28) of the lignite. The results could be resulted from the enhancement of aromatization [57,58]. 3.3.2. FT-IR analysis All samples before and after the experimental simulation were tested by means of FT-IR. The results are shown in Fig. 6. Curve fitting technology was used to quantitatively analyze the infrared structural parameters. The Peak fit (4.12) program was applied to separating the overlapping absorption peaks and calculating the peak areas. Based on a reported method [59–62], each infrared spectra was divided into four wavenumber bands (Fig. 7), including the hydroxyl absorption band (3600–3000 cm−1 [63]), aliphatic absorption band (3000–2800 cm−1 [59]), oxygen-containing functional group absorption band (1800–1000 cm−1 [64]), and aromatic absorption band (900–700 cm−1 [65]). The positions and origins of the absorption bands were established based on published literatures [62,66–68], and the fitting residuals were all maintained within 0.001. The assignment, centers, widths, heights, and areas of the peaks are shown in Table 7. To directly observe the chemical and structural changes of coal samples caused by microbes in this experimental simulation, several parameters related to infrared structure were introduced here: the hydrogen aromaticity (I1 [59]), condensation of aromatic rings (I2 [60]), branching degree of aliphatic chains (I3 [69]), deoxy index (I4 [70]), and hydroxyl content (I5 [71]). As an example, the infrared structural parameters for the L-BZ-1 sample are described as follows:

(1)

In this equation, CBi is conversion rate of CAA into biogas, mL/g; Ti1 is total biogas production in raw coal groups, mL; Ti2 is total biogas production in extracted coal groups, mL; EYi is extraction yield of CAA coal samples, %; 24 represents weight of coal samples in experimental simulation, g. 3.3. Coal chemical structure 3.3.1. Raman analysis As shown in Fig. 5, peak fitting was used to the Raman analyses of four raw coal samples and their corresponding residual samples. Five peaks can be fitted in the first-order bands, and they are bands D1, D2, D3, D4 and G [52,53]. Bands D1 and G are major bands, which can be used to characterize the microcrystalline structure of coal [54–56]. G band, which appears at ∼1580 cm−1, is assigned to the graphitic lattice vibration mode with E2g symmetry. D1 band at ∼1360 cm−1 is attributed to a disordered graphitic lattice vibration mode with A1g symmetry. The results of peak fitting were listed Table 6. The coal 216

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Intensity

(a) L-BZ-1

Raw Sum Baseline D1 G D3 D4 D2

600 400 200

1200 800 400 0

0 800

1000

600 400 200

1400

1600

1800

(c) L-LJ-1

Raw Sum Baseline D1 G D3 D4 D2

800

Intensity

1200

800 1000

500

0 1000

1200

Intensity

1000

1200

Raw Sum Baseline D1 G D3 D4 D2

(b) L-BZ-1*

1400

1600

1800

(d) L-LJ-1*

0

800

1200

400

1600

1800

(e) B-PY-1

Raw Sum Baseline D1 G D3 D4 D2

800

1400

800 1600 1200 800 400

1000

1200

Raw Sum Baseline D1 G D3 D4 D2

1400

1600

1800

(f) B-PY-1*

0

0 800

Intensity

Raw Sum Baseline D1 G D3 D4 D2

1000

1200

1000

1600

1800

(g) B-XJ-1

Raw Sum Baseline D1 G D3 D4 D2

2000

1400

800 1200 800 400 0

0 800

1000

1200

1400

1600

800

1800

1000

1200

Raw Sum Baseline D1 G D3 D4 D2

1000

1200

1400

1600

1800

(h) B-XJ-1*

1400

1600

1800

Wavenumer (cm-1)

Wavenumer (cm-1)

Fig. 5. Peak fitting for Raman spectrum of all coals before and after the simulation experiment. Table 6 Peak parameters in peak fitting of Raman spectrum. Sample

L-BZ-1 L-BZ-1* L-LJ-1 L-LJ-1* B-PY-1 B-PY-1* B-XJ-1 B-XJ-1*

Peak D1

I1 =

Peak G

P(G-D1)

Pos.

Area

FWHM

Pos.

Area

FWHM

1343 1350 1357 1358 1354 1357 1348 1350

104,382 137,666 112,597 91,856 150,617 178,970 328,754 168,260

191 161 188 150 181 154 190 180

1579 1577 1584 1580 1584 1583 1586 1583

66,201 164,184 98,242 104,016 124,255 197,947 267,839 142,027

115 126 114 117 108 113 105 111

235.71 226.78 226.85 222.00 230.21 226.35 237.50 232.93

ID1/IG

I2 =

1.58 0.84 1.15 0.88 1.21 0.90 1.23 1.18

I3 =

I4 = I5 =

Pos. is peak position, cm−1; FWHM is full wave at half maximum, cm−1; P(GD1) is peak separation between G and D1 peaks, cm−1; ID1/IG is intensity ratio of between D1 and G peaks, which is obtained by peak area ratio.

A (3000

A (900 700cm 1) 2800cm 1) + A(900

700cm 1)

A (900 700cm 1) A (1631cm 1) + A(1571cm 1)

(2) (3)

A (2934cm 1) + A(2917cm 1) + A(2849cm 1) A (2972cm 1) + A(2962cm 1) + A(2949cm 1) + A(2878cm 1) + A(2864cm 1)

(4)

A (1800 1650cm 1) A (1800 - 1650cm 1) + A(1631cm 1) + A(1571cm 1)

(5)

A (3600

3200cm 1) Atotal

(6)

When it is assumed that only aliphatic hydrogen and aromatic hydrogen are contained in coal, I1 can be calculated by the ratio of the content of aromatic hydrogen to total hydrogen (Eq. (2)). The A(900–700 cm−1) is the peak area of the absorption band that is attributed to the out-of-plane deformation vibration of aromatic 217

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stretching vibrations of CH2, and the peaks at 2972 cm−1, 2962 cm−1, 2949 cm−1, 2878 cm−1, and 2864 cm−1 correspond to symmetric and asymmetric stretching vibrations of CH3. I4 is used to determine the changes in the oxygen-containing functional groups, where the peaks at 1800–1650 cm−1 is attributed to the stretching vibrations of the C]O functional groups. I5 reflects the relative abundance of hydroxyl groups, where Atotal is the total peak areas of all functional groups. Using the above equations, the infrared structural parameters for the 16 samples were calculated, and the results are shown in Table 8.

B-XJ-2* B-XJ-2 B-XJ-1* B-XJ-1

Absorbance (a.u.)

B-PY-2* B-PY-2 B-PY-1* B-PY-1

3.3.3. XPS analysis As shown in Fig. 8, XPS survey scan and high resolution scan were carried out in four raw coals and four residual coals after simulation experiment. The raw lignite L-BZ-1 and L-LJ-1 have more oxygen, at 34.68% and 37.10% than bituminous coals (B-PY-1, 20.89%; B-XJ-1, 18.25%). It could be because the hydroxyl and carboxyl oxygen enriched in the lignite [72,73]. Sulfur content in all coals ranges from 0 to 0.34% and low content leads to not obtain a clear high resolution scan XPS for sulfur. Peak fitting was used to analyze C1s, O1s and N1s spectrum (Fig. 9), and the results were listed in the Table 9. Peaks at binding energies near 284.7 eV, 286.0 eV, and 288.2 eV correspond to the following groups: CeC or CeH (aromatics or alkanes), CeO (alcohol, phenol or ether) and COOH (carboxyl) [73,74]. The O1s peaks of the lignite could be fitted to two different oxygen functional groups: CeO near 532.6 eV and COOH near 534.6 eV [75,76]. Nitrogen form in the studied coal samples mainly consists of three types: N-5 (pyrrole nitrogen), N-6 (pyridine nitrogen) and N-Q (nitrogen oxide). The lignite L-BZ-1 and L-LJ-1 have a 17.2% and 4.1% of carboxyl content, but not in bituminous coals. Previous studies showed that carboxyl is abundant in low rank coals and slowly declines as coal rank raise [77,78]. The loss of oxygencontaining groups can result in a decrease in the N-Q peak accompanied by an increase in the N-6 peak [79].

L-LJ-2* L-LJ-2 L-LJ-1* L-LJ-1 L-BZ-2* L-BZ-2 L-BZ-1* L-BZ-1

1000

2000

3000

4000

-1

Wavenumber (cm ) Fig. 6. Infrared spectra of coal samples before and after experimental simulation. The symbol * represents the samples after the experimental simulation.

structures, and A(3000–2800 cm−1) corresponds to the peak area of the absorption band that results from the stretching vibrations of aliphatic structures. In the Eq. (3), the wavenumbers 1631 cm−1 and 1571 cm−1 both correspond to the skeletal vibrations of C]C bonds in aromatic rings. I3 is used to evaluate the degree of length and branching of aliphatic side-chains. The peaks at 2934 cm−1, 2917 cm−1 and 2849 cm−1 can be identified as the symmetric and asymmetric

0.006

(a) 3600-3000 cm-1

0.012

Raw spectrum Sum of fit peaks Fit peaks

0.008 0.004

Absorbance (a.u.)

Absorbance (a.u.)

0.016

(b) 3000-2800 cm-1 Raw spectrum Sum of fit peaks Fit peaks

0.005 0.004 0.003 0.002 0.001 0.000

0.000 3600 3500 3400 3300 3200 3100 3000

3000

-1

0.0012

Raw spectrum Sum of fit peaks Fit peaks

0.010 0.005

Absorbance (a.u.)

Absorbance (a.u.)

0.020 0.015

2850

2800

Wavenumber (cm )

(c) 1800-1000 cm-1

0.025

2900

-1

Wavenumber (cm ) 0.030

2950

0.000

Raw spectrum Sum of fit peaks Fit peaks

0.0010 0.0008

(d) 900-700 cm-1

0.0006 0.0004 0.0002 0.0000

1800

1600

1400

1200

1000

900

-1

850

800

750 -1

Wavenumber (cm )

Wavenumber (cm )

Fig. 7. Curve fittings of the L-BZ-1 sample’s infrared spectrum for different wavenumber bands. 218

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Table 7 Parameters of fitted peaks from L-BZ-1 sample’s infrared spectrum. Peak No.

Center (cm−1)

Height

Width (cm−1)

Assignment

Area (A)

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

3611.8 3545.1 3478.8 3427.7 3367.1 3233.1 2972.0 2962.1 2949.3 2933.8 2917.2 2895.2 2878.4 2863.9 2848.9 2838.8 2830.2 2820.1 1721.9 1693.8 1631.1 1571.3 1460.9 1444.6 1426.9 1375.8 1297.3 1266.9 1223.3 1197.3 1167.2 1098.7 1043.5 1030.2 1007.4 907.6 882.5 865.5 858.3 834.0 824.5 817.2 810.8 801.0 779.5 749.3 719.6 694.0

0.0044 0.0099 0.0108 0.0046 0.0066 0.0007 0.0002 0.0006 0.0010 0.0016 0.0052 0.0020 0.0010 0.0011 0.0030 0.0009 0.0005 0.0002 0.0096 0.0095 0.0260 0.0123 0.0014 0.0023 0.0017 0.0019 0.0011 0.0033 0.0022 0.0018 0.0018 0.0008 0.0022 0.0026 0.0038 0.0002 0.0002 0.0001 0.0001 0.0002 0.0006 0.0005 0.0005 0.0006 0.0009 0.0008 0.0001 0.0004

59.8 89.0 80.6 60.9 112.4 68.6 16.4 15.0 16.4 16.4 23.5 18.5 17.1 16.4 16.4 16.4 16.4 16.4 48.9 42.5 86.7 59.1 19.1 26.5 40.2 31.6 36.6 48.9 48.9 48.9 38.7 24.6 23.4 19.0 29.3 22.1 18.8 10.8 9.7 12.2 11.6 9.7 11.8 19.0 31.9 27.7 14.8 20.9

Stretching vibration of Free OH groups Stretching vibration of OH-π hydrogen bonds Stretching vibration of OH-π hydrogen bonds Stretching vibration of Self-associated OH Stretching vibration of OH-ether O hydrogen bonds Tightly bound cyclic OH tetramers Asymmetric stretching vibration of CH3 Asymmetric stretching vibration of CH3 Asymmetric stretching vibration of CH3 Asymmetric stretching vibration of CH2 in alkanes Asymmetric stretching vibration of CH2 in alkanes Stretching vibration of CH in alkanes Symmetric stretching vibration of CH3 Symmetric stretching vibration of CH3 Symmetric stretching vibration of CH2 in alkanes Stretching vibration of CH in aldehyde group Stretching vibration of CH in aldehyde group Stretching vibration of CH in aldehyde group Stretching vibration of C]O in conjugated esters Stretching vibration of C]O in carboxylic acids Skeletal vibration of C]C in aromatic rings Skeletal vibration of C]C in aromatic rings Asymmetric deformation vibrations of CH3 and CH2 Asymmetric deformation vibration of CH3 and CH2 Asymmetric deformation vibration of CH3 and CH2 Symmetrical bending vibration of CH3 Asymmetric stretching vibration of CeOeC in cyclic ethers Stretching vibration of CeOH in phenols Asymmetric stretching vibration of CeOeC in aromatic ethers Stretching vibration of CeOH in phenols Stretching vibration of CeOH in phenols Asymmetric stretching vibration of SieOeSi in quartzes Symmetric stretching vibration of CeOeC in alkyl ethers Stretching vibration of SieO in aluminosilicates Stretching vibration of SieO in aluminosilicates Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures Out-of-plane deformation vibration of aromatic structures

0.2828 0.9327 0.9288 0.3000 0.7903 0.0486 0.0032 0.0093 0.0177 0.0283 0.1295 0.0397 0.0190 0.0199 0.0517 0.0150 0.0084 0.0038 0.4971 0.4296 2.3982 0.7746 0.0281 0.0655 0.0710 0.0646 0.0421 0.1703 0.1147 0.0934 0.0752 0.0222 0.0536 0.0518 0.0833 0.0012 0.0043 0.0012 0.0009 0.0032 0.0070 0.0053 0.0062 0.0129 0.0296 0.0248 0.0020 0.0021

4. Discussion

Table 8 Infrared structural parameters of 16 samples. Samples

I1

I2

I3

I4

I5

L-BZ-1 L-BZ-1* L-BZ-2 L-BZ-2* L-LJ-1 L-LJ-1* L-LJ-2 L-LJ-2* B-PY-1 B-PY-1* B-PY-2 B-PY-2* B-XJ-1 B-XJ-1* B-XJ-2 B-XJ-2*

0.2254 0.3038 0.4254 0.4863 0.2336 0.3277 0.3566 0.3549 0.3070 0.3823 0.4017 0.4723 0.2685 0.3416 0.3792 0.4135

0.0317 0.0321 0.0923 0.0417 0.1584 0.1136 0.0867 0.0847 0.2497 0.2996 0.3925 0.2503 0.2104 0.2408 0.3355 0.2439

4.0701 2.9245 1.8336 1.5418 3.4212 2.8276 1.3021 0.8837 2.5372 1.8493 2.1447 1.7112 2.3212 2.0939 2.3132 1.1564

0.2260 0.4450 0.2552 0.3441 0.3648 0.3240 0.1612 0.0613 0.2063 0.1190 0.1764 0.0174 0.1181 0.0169 0.0706 0.0324

37.4607 13.6276 42.5942 17.8156 51.6570 8.3066 68.5939 11.1421 49.4138 31.9678 45.4780 16.1007 31.7987 22.7264 24.4826 22.7915

4.1. Relation between organic matter and biogas production Published literatures have shown that the organic matter in coal can provide energy and carbon sources for microorganisms [5,32,35,80]. The types and abundance of organic matter can affect biogas production and yield [34,81]. The effect characteristics can be determined by analyzing the correlation between biogas production and compositions of organic matter in the experimental simulation. The cumulative biogas production can be calculated using the Eq. (7), (8), and (9), and the results for the six raw coal groups (L-BZ-1, L-LJ-1, B-PY-1, B-PS-1, BXJ-1, and B-ZJ-1) are 176.85 mL, 226.59 mL, 148.76 mL, 136.30 mL, 145.60 mL, and 181.67 mL, respectively. Biogas production in the lignite groups is higher than that in the bituminous coal groups. This negative correlation between biogas production and coal rank has been observed in previous studies [29,32,80]. It is widely recognized that low rank of coal is more easily biodegraded resulting from a lower degree of condensation and structural heterogeneity [32,82–84]. Robbins et al. [32] found that methane yield was positively correlated with 219

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Counts (s)

160000 120000

C1s

80000

N1s

40000

Counts (s)

120000

0

62.19 34.68 2.95

Name C1s O1s N1s S2p

80000 40000

Atomic (%) 58.67 37.10 3.14 0.14

120000

120000

0

200 400 600 800 1000 1200 1400

Name C1s O1s N1s S2p

(d) L-LJ-1*

90000 60000 30000

-200

200 400 600 800 1000 1200 1400

Name C1s O1s N1s S2p

(e) B-PY-1

40000

Atomic (%) 75.96 20.89 2.99 0.16

0

Atomic (%) 75.18 20.53 3.95 0.34

200 400 600 800 1000 1200 1400

Name C1s O1s N1s S2p

(f) B-PY-1*

160000 120000 80000 40000

0

Atomic (%) 82.34 14.39 2.67 0.19

0

-200

120000

0

0

80000

160000

Atomic (%) 75.66 21.59 2.64 0.11

S2p

-200

0

160000

Name C1s C1s O1s O1s N1s N1s S2p

(b) L-BZ-1*

100000 80000 60000 40000 20000 0

200 400 600 800 1000 1200 1400

(c) L-LJ-1

-200

Counts (s)

C1s O1s N1s

0 -200

Counts (s)

O1s Name Atomic (%)

(a) L-BZ-1

0

200 400 600 800 1000 1200 1400

Name C1s O1s N1s S2p

(g) B-XJ-1

80000 40000

Atomic (%) 78.56 18.25 2.91 0.11

-200

0

200 400 600 800 1000 1200 1400

Name C1s O1s N1s S2p

(h) B-XJ-1*

160000 120000 80000 40000

0

Atomic (%) 81.75 14.12 3.90 0.24

0

-200

0

-200

200 400 600 800 1000 1200 1400

0

200 400 600 800 1000 1200 1400

Binding energy (eV)

Binding energy (eV)

Fig. 8. XPS survey scans of all coals before and after the simulation experiment.

Counts (s)

12000

8000

(a) C1s

Baseline Raw Sum Peak1 Peak2 Peak3

8000 4000

1800

(b) O1s

Baseline Raw Sum Peak1 Peak2

6000 4000 2000

(c) N1s

Baseline Raw Sum Peak1 Peak2

1600

1400

0 280

285

290

295

Binding energy (eV)

300

525

530

535

540

545

392

Binding energy (eV)

396

400

404

408

Binding energy (eV)

Fig. 9. Peak fitting of XPS high resolution scan in L-BZ-1: (a) C1s spectra, (b) O1s spectra, (c) N1s spectra.

amounts of volatile fatty acids, which are enriched in low rank of coals. Comparing with lignite, bituminous coal has lower levels of heteroatoms and a higher condensation of aromatic structure [26]. The increase in aromaticity was accompanied by a loss of heteroatom amenable to microbial attack, resulting in reducing bioavailability. Accordingly, it has been considered that lower rank of coal is more bioavailable and has more biogas production than higher rank of coal

[26,29].

P b (KB )

(7)

Pt × (100 C(N2)) 100

(8)

Pnet = P b (EG )

Pb =

220

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Table 9 Peak parameters and attribution in peak fitting of XPS high resolution scan. Name

L-BZ-1

L-BZ-1*

L-LJ-1

L-LJ-1*

Attribution

Pos.

Area

RC

Pos.

Area

RC

Pos.

Area

RC

Pos.

Area

RC

C1s

284.7 285.9 288.2

14347.5 6815.1 4411.4

56.1 26.6 17.2

284.7 285.8 288.5

13603.4 8337.3 1171.2

58.9 36.1 5.1

284.8 286.0 288.9

13132.2 7139.9 384.6

63.6 34.6 1.9

284.6 286.0 288.4

11741.7 3788.0 669.1

72.5 23.4 4.1

C–C or C–H C-O COOH

O1s

532.5 534.6

13887.7 3477.7

80.0 20.0

532.5 n.d.

15609.2 n.d.

100 n.d.

532.6 534.7

27463.5 3616.4

88.4 11.6

532.4 n.d.

26594.8 n.d.

100 n.d.

C-O COOH

N1s

400.3 402.1

523.9 50.1

91.3 8.7

400.2 n.d.

1348.3 n.d.

100 n.d.

400.2 402.7

815.7 159.7

83.6 16.4

400.1 n.d.

1162.9 n.d.

100 n.d.

N-5 N-Q

Name

B-PY-1

B-PY-1*

B-XJ-1

B-XJ-1*

Attribution

Pos.

Area

RC

Pos.

Area

RC

Pos.

Area

RC

Pos.

Area

RC

C1s

284.8 286.2

22885.0 7463.1

75.4 24.6

284.8 286.1

25066.3 5669.2

81.6 18.4

284.8 285.6

18967.9 7269.5

72.3 27.7

284.7 285.6

20285.2 5854.0

77.6 22.4

C–C or C–H C–O

O1s

532.8

13601.9

100

532.8

10345.1

100

532.8

15309.9

100

532.7

12108.7

100

C–O

N1s

398.5 400.2

101.7 1058.1

8.8 91.2

n.d. 400.4

n.d. 1524.8

n.d. 100

398.7 400.3

91.6 522.5

14.9 85.1

n.d. 400.4

n.d. 2029.7

n.d. 100

N-6 N-5

Pos. is peak position, eV; RC is percentage of peak area, %; n.d. is no data.

containing hydrogen and oxygen are required for biogas generation. The CAA is defined as the amount of organic matter that is extracted from coal by chloroform. The abundance of soluble organic matter was often used to evaluate the hydrocarbon generating potential of source rocks [87–89]. Low and medium rank of coals are rich in soluble organic matter, which can be utilized by microorganisms and eventually form precursors of biogas [24,90]. Four treated coal groups (L-BZ-2, L-LJ-2, BPY-2, and B-XJ-2) have a similar cumulative regularity in their headspace gas as that of the control group (KB), and their accumulation is obviously lower than that of the four corresponding raw coal groups (Table 5). It is suggested that soluble organic matter provides the main source of material for biogas generation. In the six raw coal groups, the strong positive correlation between biogas production and the CAA extraction yield (Fig. 12a, R2 = 0.83) supports this conclusion. The organic part of coal is composed of solid kerogen infused with solvent-extractable matter or bitumen that is filled in the pores and cleats [91,92]. It is widely accepted that the extractable materials with a smaller molecular size and higher mobility are more degradable since they are not chemically bonded to the carbon skeleton of the coal [7,93]. With different molecular structures, several components of CAA have differences in bioavailability. As shown in Fig. 12b-c, biogas production is positively correlated with the saturated hydrocarbons or nonhydrocarbons content. Biodegradation of alkanes in saturated hydrocarbons has been observed [94]. Furmann et al. [93] used dichloromethane-soluble organic matter that was extracted from coal as

t

Qnet =

Pnet

(9)

i=0

In the aforementioned equations, Pt is the production of headspace gas, mL; Pb is the production of biogas, mL; C(N2) is the nitrogen content in Fig. 3, %; Pnet is the production of biogas generated by consumption of coals in the experimental groups, mL; Pb(EG) is the Pb values of the experimental groups, mL,; Pb(KB) is the Pb values of the control group, mL; Qnet is the accumulation of Pnet, mL; t is the duration of the experimental simulation, d, t ≤ 90. As shown in Fig. 10, in the six raw coal groups, there is a positive correlation between biogas production and the amounts of moisture and volatile matter in coals. The volatile matter is mainly derived from small molecule compounds that arise in the breakdown of unstable fatty side chains and oxygen-containing functional groups in coal [85]. In general, as the coal rank increases, the amounts of moisture and volatile matter decrease [86]. Fallgren et al. [5] found that bioactivity increased with the increase of volatile organic matter content in coal, and bioavailability is closely related to the low maturity of organic matter, essentially. The positive correlation between biogas production and the atomic ratio of hydrogen to carbon or oxygen to carbon could indicate that hydrogen- and oxygen-rich substances are the main raw materials for biogas production (Fig. 11). Hydrogenotrophic and acetoclastic methanogenesis are two common processes involved in biogas generation [26], which demonstrates that large amounts of organic matter

(a)

200

160

120

R2 = 0.56

0

2

4

6

8

(b)

240

Qnet (mL)

Qnet (mL)

240

10

Mad (%)

200

R2 = 0.4 160

120

30

35

40

Vdaf (%)

Fig. 10. Correlation of cumulative biogas production and (a) Mad, (b) Vdaf. 221

45

50

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(a)

220

220

200

200

180 160

R2 = 0.83

140 120

(b)

240

Qnet (mL)

Qnet (mL)

240

180 160 140

0.76

0.80

0.84

120

0.88

Atomic ratio of hydrogen to carbon (H/C)

0.08

0.12

0.16

0.20

Atomic ratio of oxygen to carbon (O/C)

Fig. 11. Correlation of the cumulative biogas production and (a) H/C, (b) O/C.

the sole carbon source in the microbial methanogenesis process, and the results showed that n-alkanes in coal extracts are significantly biodegraded. Aliphatic hydrocarbons can be biodegraded and produce a large number of fatty acids that can directly provide sufficient substrates for methanogenic microbes [26]. Wang [95] reported that nonhydrocarbons consist of heteroatom compounds containing oxygen, nitrogen and sulfur atoms. These heteroatom compounds may contain more activation sites either within heterolinkages (e.g., ester bonds) or neighboring CeC bonds (e.g., hydroxyl groups), which may facilitate microbial cleavage [36,96–98]. However, asphaltene, which is a complex polymer organic compound, is hardly biodegradable. When the amount of asphaltene is high, it is not conducive to biogas generation (Fig. 12d). This may be attributed to the delocalization of the π

240

(a)

200

Qnet (mL)

Qnet (mL)

240

electrons making aromatic ring structure more stable [36]. Biogas production was negatively correlated with the n-C21−/n-C22+ ratio in n-alkanes (Fig. 12e). Long-chain n-alkanes exhibit a high bioavailability. However, it is generally accepted that short-chain n-alkanes derived from lower aquatic organisms are more substantially degraded than long-chain n-alkanes derived from higher aquatic or terrestrial plants [89,90]. This could be because n-alkanes are not the only organic matter source that supports microbial methanogenesis, and other substances can also serve as sources (e.g., the abovementioned nonhydrocarbons). The greater proportion of short-chain n-alkanes in the four high-volatile bituminous coals may explain why the peak of gas production in the bituminous coal group preceded that of the lignite group in the early stages of the experiment (Fig. 13). As shown in Fig. 12f, there is a strong positive

R2 = 0.83

160 120 2.0

2.2

2.4

2.6

2.8

200 160 120

3.0

(b)

R2 = 0.42 0

Extraction yield of chloroform bitumen (%) 240

(c)

200 160 120

Qnet (mL)

Qnet (mL)

240

R2 = 0.75 30

35

40

45

4

160

R2 = 0.57 10

20

2

R = 0.73

Qnet (mL)

Qnet (mL)

240

0.3

0.4

n-C21-/n-C22+

30

40

50

60

Asphaltenes content (%)

160 120 0.2

16

200

120

50

(e)

200

12

(d)

Non-hydrocarbons content (%) 240

8

Saturated hydrocarbons content (%)

0.5

(f)

200 160 120 0.8

R2 = 0.66 1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

CPI

Fig. 12. Correlation between the cumulative biogas production and (a) CAA, (b) Saturated hydrocarbons, (c) Non-hydrocarbon, (d) Asphaltenes, (e) n-C21−/n-C22+, (f) CPI. 222

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Accumulation of headspace gas (mL)

P. Shao, et al.

fewer fused rings are preferentially degraded [17,100]. In the FT-IR analysis, the lignite (L-BZ-1 and L-LJ-1) has the higher I3 and I4 values and lower I1 and I2 values than the bituminous (B-PY-1 and B-XJ-1) (Fig. 14a-d), which suggested that lignite contains more aliphatic chains and oxygen-containing functional groups and lower degree of aromatic condensation. Compared to the raw coals, I1 and I2 values of the treated coals raise, and I3 and I4 values show opposite. This indicated that the chemical structure of the CAA in coals mainly consists of aliphatic chains and oxygen-containing functional groups. At the end of the experimental simulation, the residual coals have the higher I1 and I2 values and lower I3 and I4 values than the raw coals. This characteristic showed that a large number of organic materials with aliphatic chains and oxygen-containing functional groups were consumed by microbes to produce biogas, which is in line with the conclusion that saturated hydrocarbons and nonhydrocarbons in CAA are more susceptible to biodegradation. The obvious decrease of I5 further confirmed that hydroxyl group is an important oxygen-containing functional group for biogas generation (Fig. 14e). In experimental simulation, 63.6% and 83.9% of hydroxyl groups in lignite (LBZ-1 and L-LJ-1) were consumed, and bituminous coals were less than 40%. This obvious different may be caused by the different pathway of biogas generation occurred in different experiment groups. The previous research has shown that biogas was produced mainly by acetoclastic methanogenesis, but the presence of hydrogenotrophic methanogenesis was also demonstrated in the lignite group [39]. The accumulation of headspace gas in the treated coal group is higher than that in the control group (Table 5), which demonstrates that treated coals are subjected to biodegradation during the production of biogas. As a result of microbial action, aromatic condensation of the four treated coal groups is reduced rather than elevated (Fig. 14b). It has been indicated that the aromatic skeleton structure can serve as a substrate to be biodegraded. Therefore, in the late stages of the experimental simulation, it was found that biogas production began to rise (Fig. 13). Wang et al. [90] found that the process underlying the formation of secondary biogenic coalbed methane can be divided into two periods: the first period is the gas production stage that involves huminite and liptinite, and the second period is the biodegradation stage that involves inertinite. This result is consistent with the Raman analysis. In XPS analysis, it can be found that four residual coals have an obvious decrease in oxygen content and an increase in carbon content after the simulation experiment (Fig. 8). For example, oxygen content in L-BZ-1 decreases from 34.68% to 21.59% and carbon content increases from 62.19% to 75.66%. The result indicates that substances containing oxygen functional groups in raw coals are easily attacked by

600 500 400 300 200

KB L-BZ-1 L-LJ-1 B-PY-1 B-XJ-1

100 0 10

20

30

40

50

L-BZ-2 L-LJ-2 B-PY-2 B-XJ-2

60

70

80

90

Time (d) Fig. 13. Accumulation of headspace gas in the experimental simulation.

correlation between biogas production and the CPI, which implies that nalkanes with odd carbon numbers are more easily biodegraded than nalkanes with even carbon numbers. This coincided with previous research that n-alkanes with odd carbon numbers are gradually degraded into nalkanes with even carbon numbers and the CPI will gradually approach 1 as the degree of evolution increases [89]. 4.2. Changes of coal chemical structure in experimental simulation Comparing the Roman results of each coal before and after the simulation experiment, the dominant difference was the decrease in the FWHM-D1, P(G-D1), and ID1/IG and an increase in the FWHM-G. Taking L-BZ-1 for an example, microbial activity decreased FWHM-D1 from 191 cm−1 to 161 cm−1, P(G-D1) from 235.71 cm−1 to 226.78 cm−1, ID1/IG from 1.58 to 0.84, and raised FWHM-G from 115 cm−1 to 126 cm−1. The decrease of FWHM-D1 and ID1/IG indicated an increase of ordering degree of all residual coals after the simulation experiment, which may be resulted from the microbial degradation of small molecular substances in coal such as aliphatic and oxygen-containing functional group compounds. The decrease of P(G-D1) and increase of FWHM-G in all residual coals, reflecting an increase of disordered degree of lattice structure, is probably caused by biodegradation of aromatic structures. In subsurface coal ecosystems, it can be found that aromatics in coal were biodegraded [99]. Aromatic compounds with

(c)

(b)

(a)

B-XJ-2* B-XJ-2 B-XJ-1* B-XJ-1

(d)

(e)

B-PY-2* B-PY-2 B-PY-1* B-PY-1 L-LJ-2* L-LJ-2 L-LJ-1* L-LJ-1 L-BZ-2* L-BZ-2 L-BZ-1* L-BZ-1 0.0

0.2

I1

0.4

0.6 0.0

0.2

0.4

0

1

2

I3

I2

3

4

0.0

0.2

I4

0.4

0

20

40

60

I5

Fig. 14. Bar graph of infrared structural parameters of 16 samples before and after experimental simulation. The symbol * represents the samples after the end of experimental simulation. 223

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microorganisms. From C1s and O1s peak regions, it was found that biodegraded oxygen-containing functional groups are C-O and COOH for lignite, but only C-O for bituminous (Table 9). The N-Q in the liginite and N-6 in bituminous coals was depleted after the experiment (Table 9). Li et al. [101] found that methanogenic bacteria can degrade nitrogen-containing heterocyclic compounds into small molecular organic acids. Strąpoć et al. [26] confirmed that macerals enriched in heteroatom are more biodegradable, which was indicated by the bond dissociation energies: 365 kJ/mol for C–C, 344 kJ/mol for C-O, 342 kJ/ mol for C-N [102].

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5. Conclusions Experiment simulation of biogas generation was performed using lignite, high-volatile bituminous coals and residual coal samples extracted by chloroform as substrates over a 90-day period. The Raman, FT-IR and XPS analysis was used to compare chemical structural changes of coal before and after the experimental simulation. Following conclusions can be drawn: (1) The lignite shows greater hydrocarbon-generating potential than high-volatile bituminous coal in this study. In 90 days, gas production in lignite groups (L-BZ-1 and L-LJ-1) is 12.6% more than the bituminous coal groups in the experiment simulation. This is attributed to more soluble organic matter in the lignite. For the chemical structure, the lignite has more aliphatic and oxygen-containing functional groups. (2) The CAA in coal plays an important role in microbial metabolism to produce biogas. It has a conversion rate of 3.08 mL/g on average into biogas in this experimental simulation. The saturated hydrocarbons and nonhydrocarbons are the most important components in the CAA for biogas production. The n-alkanes with shorter chains or an odd carbon number are preferentially degraded. (3) Chemical structures rich in heteroatoms are most vulnerable to microbial attack (e.g. OH, COOH, and N-Q in lignite, C-O and N-6 in bituminous coal). Aliphatic compounds have advantages over aromatics in biodegradation. In the later stage of biogas generation, the aromatic structure in coal is also degraded slightly. Acknowledgements This study was supported by Outstanding Innovation Scholarship for Doctoral Candidate of “Double First Rate” Construction Disciplines of CUMT. The authors would like to thank the anonymous reviewers for their detailed and constructive comments on this manuscript. References [1] Park YS, Liang Y. Biogenic methane production from coal: a review on recent research and development on microbially enhanced coalbed methane (MECBM). Fuel 2016;166:258–67. [2] Bumpus JA, Senko J, Lynd G, Morgan R, Sturm K, Stimpson J, et al. Biomimetic solubilization of a low rank coal: implications for its use in methane production. Energy Fuels 1998;12:664–71. [3] Breckenridge CR, Polman JK. Solubilization of coal by biosurfactant derived from Candida bombicola. Geomicrobiol J 1994;12:285–8. [4] Barnhart EP, De León KB, Ramsay BD, Cunningham AB, Fields MW. Investigation of coal-associated bacterial and archaeal populations from a diffusive microbial sampler (DMS). Int J Coal Geol 2013;115:64–70. [5] Fallgren PH, Zeng C, Ren Z, Lu A, Ren S, Jin S. Feasibility of microbial production of new natural gas from non-gas-producing lignite. Int J Coal Geol 2013;115:79–84. [6] Gilcrease PC, Shurr GW. Making microbial methane work: the potential for new biogenic gas. World Oil 2007;228:1–48. [7] Jones EJP, Voytek MA, Corum MD, Orem WH. Stimulation of methane generation from nonproductive coal by addition of nutrients or a microbial consortium. Appl Environ Microbiol 2010;76:7013–22. [8] Grethlein HE, Karkalits OC, Kern EE, Leuschner AP, Menger WM, Odelson D. Microbial process for producing methane from coal. US, US 6143534 A, 2000. [9] Ritter D, Vinson D, Barnhart E, Akob DM, Fields M, Cunningham W, et al. Enhanced microbial coalbed methane generation: a review of research,

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