Skip to main content
NCBI home page
ACS Omega logoLink to ACS Omega
. 2025 Jun 17;10(25):26368–26381. doi: 10.1021/acsomega.4c09939

Experimental Investigation on the Migration of Contaminant Generated in the Dry Distillation Channel to Overburden during Underground Coal Gasification

Lin Xin †,‡, Weihao Xu †, Maofei Niu †,*, Mingze Feng †, Min Yang †, Hualong Li †, Zhenjie Shang †, Xin Wang †
PMCID: PMC12223826  PMID: 40621045

Abstract

Underground coal gasification (UCG) is a promising technique to develop coal resources efficiently and environmentally. However, contaminants generated from pyrolysis in the dry distillation channels during the UCG process have the risk of migration to the overburden, resulting in the potential contamination of groundwater. In this study, a new experiment was designed and carried out using overlying rock samples. By combining Fourier transform infrared spectrometry (FTIR) and X-ray diffraction (XRD) analysis, the composition of contaminants, including organic and inorganic contaminants, was identified. The migration behavior of contaminants in the overburden was revealed. The results showed that the overburden has a strong adsorption of heavy metals and porosity is an important factor affecting the migration of heavy metals. The adsorption capacity of the overburden for benzene and oxygen-containing functional group contaminants is weak, and the migration abilities of benzene and oxygen-containing functional group contaminants are approximately the same in short-range migration. The main form of benzene contaminants is pentasubstituted benzene, and changes in its relative content are negatively correlated to trisubstituted and disubstituted benzene. Oxygen-containing functional group contaminants mainly consist of alcohols, phenols, and ethers, which have strong mobility in the overburden and are the main substances in contaminants. The migration ability of Mn is the greatest among inorganic heavy-metal contaminants, followed by those of Pb, Cu, and Cd. The research provides a theoretical basis for the prevention and control of contaminants during industrial application of UCG.

graphic file with name ao4c09939_0014.jpg

graphic file with name ao4c09939_0012.jpg

1. Introduction

Coal remains the predominant energy source for electricity generation, steel production, and cement making and continues to play a crucial role in the global economy. Simultaneously, coal is the primary contributor to anthropogenic carbon dioxide (CO2) emissions, and excessive CO2 and other greenhouse gases have emerged as a significant issue confronting humanity. China, as the largest consumer of coal in the world, committed to achieving carbon peak and neutrality targets at the United Nations General Assembly on September 22, 2020. This promise is substantial and will necessitate enormous transformations in China’s fossil fuel industry. Therefore, efficient and clean utilization of coal within the context of carbon neutrality holds significant practical importance. , Underground coal gasification (UCG) is a coal mining technique that integrates well construction, coal mining, and gasification. , It offers the benefits of adequate safety, inexpensive investment, and excellent efficiency. , Known as the second-generation coal mining method, UCG can be combined with carbon capture and storage technologies to reduce greenhouse gas emissions and is currently receiving widespread attention. − Due to the in situ reaction during UCG, heavy metals and organic contaminants in coal are unavoidably retained underground. − The potential risk of groundwater pollution is one of the factors restricting the development of UCG. As a promising technique for green coal mining, , UCG needs to be continuously explored to solve environmental problems. ,

Many scholars around the world have done a number of research studies on the contaminants generated by UCG. The organic matter in coal decomposes under the action of high temperatures and undergoes hydrocarbon cracking and oxidation reactions, producing many volatile substances and solid residues. There are two main ways for contaminants generated by gasification to enter groundwater. The first is that under the pressure of the combustion cavity, the contaminants migrate with coal gas in the cracks of the surrounding rock pores and eventually enter groundwater. The second is that groundwater flows into the UCG combustion cavity, and the contaminants in the ash are immersed. , Polish scholars Kapusta et al. detected the groundwater at gasification sites and found that the primary contaminants caused by UCG were phenols, aromatic hydrocarbons, ammonia nitrogen, and cyanide. Ütnü et al. conducted extensive studies on polycyclic aromatic hydrocarbons (PAHs) in the residue of Markala lignite gasification. They found that the thermal process directly affected the content of PAHs in lignite and lignite char. Pankiewicz-Sperka et al. comprehensively characterized the water after UGC. They found that the water contained many hazardous compounds, including benzene, toluene, ethylbenzene, xylene, phenols, and PAHs, and that there were large quantities of inorganic compounds in the coal and ash generated during the volatilization process. Li et al. analyzed the potential forms of arsenic and cadmium contaminants in UCG. They studied the control methods and design processes for reducing heavy-metal pollution in UCG without shafts. Campbell et al. found that 15 months after the completion of gasification in the UCG area of Hoe Creek, Wyoming, the primary organic contaminants in the groundwater 10 km away from the gasification site were phenolic compounds, with small amounts of organic contaminants such as polycyclic aromatic hydrocarbons and heterocyclic compounds. Strugala-Wilczek and others − also discovered various heavy-metal elements and radioactive substances in underground gasification ash. Professor Liu Shuqin’s team studied the volatilization pattern of mercury, arsenic, and selenium during underground coal gasification by comparing the volatilization of mercury, arsenic, and selenium during the conversion of coal to semicoke and semicoke to ash. Grabowski et al. assessed the risk of underground gasification water pollution by collecting water samples at different stages of gasification tests. They found that contaminants from gasification were classified as substances particularly harmful to the aquatic environment (including aromatic hydrocarbons, phenols, ammonia, and cyanides). Dong et al. have also studied the contaminants generated by gasification and built an ex situ experimental system of UCG to study the evolution behaviors of contaminants such as tar in the reaction zone. For the pollution caused by UCG, Sheng et al. established a hydrogeological model of the UCG process and used it to assess the environmental risks caused by contaminant transportation. In the study of contaminant migration behavior, Soukup et al. conducted a numerical simulation on the migration of contaminants in porous media after shallow UCG. They found that factors such as porosity and pore size would play an essential role in the migration of contaminants.

More studies have been conducted on quantitative and qualitative analyses of the types of organic contaminants generated by UCG, as well as more studies on direct monitoring of the groundwater near underground gasifiers and analysis of the changes in contaminant content in the groundwater near gasifiers. However, limited studies have been reported on the migration of contaminants from the gasifier into the overburden and the migration ability of different contaminants.

A series of complex redox reactions and coal pyrolysis reactions occur at the gasification reaction interface of UCG. The underground coal seam enters the reduction zone after combustion, and a heat absorption reaction occurs in the seam. The temperature in the coal seam gradually decreases as the reaction proceeds and finally reaches the dry distillation drying zone. As the moving direction of the underground gas flow is the same as the burning direction of the flame, the dry distillation pyrolysis reaction in the coal seam continues. A large number of chemical reactions accompany the coal pyrolysis process, and the resulting calorific value increases the gas content and affects the structure of the residual char in the gasification process; therefore, the study of the dry distillation drying zone is essential to reduce the contamination of groundwater. In this study, focusing on contaminants generated from coal pyrolysis in the dry distillation channel during UCG, experiments were performed using four sets of simulated overlying rocks for investigation of contamination migration. The results were carefully analyzed with the combination of standard methods, such as FTIR and XRD. Then, the types and relative contents of contaminants remaining inside the simulated overlying rock were investigated, and the migration behavior of contaminants with gas in the porous medium of the overburden was revealed.

2. Test Materials and Methods

2.1. Material Preparation

Four groups of simulated overlying rock materials were prepared using sands of different particle sizes (No. 1 0.9–1.43 mm, No. 2 0.45–0.9 mm, No. 3 0.3–0.45 mm, and No. 4 0.15–0.3 mm) as aggregates, gypsum, and cement as binders. Under the same experimental conditions, larger sand particles mean larger media porosity. 60% of the total mass of the simulated material was sand, 20% was binder, and the remaining 20% was water. Of this, cement constituted 70% of the binder mass. After stirring evenly, each group of materials was placed into PVC pipes with an inner diameter of 100 mm and a height of 120 mm, compacted and sealed with fresh-keeping film for 3 days, and then opened and dried. The preparation process of simulated overlying rock is shown in Figure .

1.

1

Open in a new tab

Preparation process of the simulated overlying rock.

The coal used in the experiments is bituminous coal in Tianjin, China. The results of the proximate and ultimate analyses of the coal sample are shown in Table . It can be seen that the degree of metamorphism of Tianjin bituminous coal is relatively high, with a carbon content of up to 81.39%, belonging to fat coal. The volatile content in bituminous coal is relatively high, making it ideal for gasification reactions to obtain synthesis gas, which is suitable for this experiment. Large pieces of Tianjin bituminous coal were selected for crushing, and the coal powder was evenly divided into four portions with a particle size of 0.3–0.45 mm, with each portion containing 50 g.

1. Proximate and Ultimate Analysis of Tianjin Bituminous Coal.

proximate analysis (wt %) ultimate analysis (wt %, daf)
M ad A d V d V daf FCd C daf H daf N daf O daf S daf
0.84 17.07 32.09 38.70 50.84 81.39 4.82 0.79 11.9 1.1
Open in a new tab

2.2. Test Setup

The main experiment is conducted using a tubular heating furnace, which works by heating the material at high temperatures to undergo pyrolysis reactions and convert it to gas, liquid, or solid products. The temperature distribution during the reaction process is as uniform as possible to ensure the stability of the reaction, and the product type and proportion can be adjusted by controlling the temperature, gas flow rate, and other conditions. The coal was pyrolyzed at a high temperature under a nitrogen atmosphere, and the generated contaminants flowed with the gas into the simulated overlying rock device to simulate the migration of contaminants in the gasification channel with coal gas in the overburden. The equipment mainly includes a gas carrier device, a gas stabilizing valve, a tubular heating furnace, simulated overlying rock, and a gas washing bottle. The connection schematic of the experimental equipment is shown in Figure .

2.

2

Open in a new tab

Schematic diagram of test equipment: 1Nitrogen cylinder; 2Flowmeter; 3Tube furnace; 4Coal samples; 5Simulated overlying rock; 6Gas washing bottle.

2.3. Test Procedures

In UCG, gas from the gasifier can migrate and contaminate overburden due to inappropriate operating scenarios or geological factors. If the gasification pressure is too high and exceeds the hydrostatic pressure of the surrounding rock, then the gas will break through the rock barrier and migrate further away. Gas has a low molecular weight and strong migration ability, and pores or fissures in the rock can also cause gas migration. The migration of gas is also affected by the temperature gradient; the gas in the high-temperature region may migrate to the lower-temperature region due to the effect of the temperature gradient, and with the expansion of the gasification area, the gas in the high-temperature region may migrate outward along the temperature gradient to penetrate the overburden. The process of gas migration to the overburden was simulated in the experiment. Bituminous coal powder was placed in a tubular heating furnace, and the equipment was connected to ensure that the system was sealed. The nitrogen flow rate was set at 400 mL/min, and the pressure of the nitrogen cylinder was set at 1.2 atm. Nitrogen was continuously introduced for 30 min to remove the residual air from the furnace. After that, the heating program was set, and the temperature was increased to a final temperature of 600 °C at a rate of 10 °C/min. After reaching the final temperature, the temperature was kept constant for 5 h with a nitrogen flow rate of 500 mL/min and a nitrogen cylinder pressure of 1.2 atm. At the end of the experiment, the nitrogen cylinder was turned off to save the simulated overlying rock.

2.4. Analysis Methods

FTIR can be used for qualitative and quantitative analysis of samples. The obtained samples were dried and ground into particles of about 75 μm. The ground samples were mixed with KBr in a ratio of 1:100 and fully ground, then put into the tableting machine to press into transparent samples with a thickness of 1 mm. The samples were placed into an infrared spectrometer (NICOLET380) with a scanning range of 4000–400 cm–1 and a resolution of 4 cm–1. The scanning frequency was 32 times, and the moving mirror speed was 0.6329. The infrared spectra of four sets of samples at different positions were collected, and then, peak division and peak area correction were performed.

The XRD experiment used Cu, Ni balanced filters, divergent slit DS = 0.9570°, antiscattering slit SS = 0.9570°, receiving slit RS = 0.3 mm, graphite bent crystal monochromator placed in the diffraction beam, tube pressure 40 kV, and tube flow 30 mA. Take 1 g of the ground sample with a medication spoon and evenly spread it in the sample slot. Place it in the Rigaku Ultima IV X-ray diffraction and set the scanning range to 5 ∼ 80° and scanning speed to 7°/min. After the parameters are set, we started testing and obtained XRD patterns.

3. Results and Discussion

3.1. Analysis Using the Observation Method

The sampling location is listed in Figure . The bottom sampling point of No. 1 simulated overlying rock was named 1–1, the middle sampling point was named 1–2, the upper sampling point was named 1–3, and so on. After the experiment, the observation method was used to study the simulated overlying rock samples. As shown in Figure , different degrees of discoloration could be observed at the bottom of the simulated overlying rock with an overall blue-green color and local yellow-brown color. From the side of the simulated overlying rock, the diffusion of yellow-brown oily contaminants along the fractures could be observed, which indicated that the contaminants diffused into the overlying rock with gas, and a large amount of tar generated by coal pyrolysis was adsorbed in the simulated overlying rock near the gas inlet end. To further study the types and distribution of residual contaminants in the overlying rock, 12 samples from four sets of simulated overlying rock were analyzed.

3.

3

Open in a new tab

Location of simulated overlying rock sampling points after the test.

4.

4

Open in a new tab

Appearance of the simulated overlying rock after the test.

3.2. Analysis of the Migration Behavior of Organic Contaminants

After pyrolysis and gasification of coal, coal gas and many types of contaminants are generated. Most contaminants remain inside the combustion cavity, and some migrate with coal gas in the overburden. FTIR is used to detect the functional groups contained in the samples and study the migration behavior of contaminants in the overburden. The FTIR spectra of samples Nos. 1–4 are shown in Figure , in which the aromatic hydrocarbon structure region of 700–900 cm–1 and the oxygen-containing functional group region of 1000–1800 cm–1 are critical for determining the changes in the types and relative content of contaminants.

5.

5

Open in a new tab

Infrared spectrum of (a) No. 1, (b) No. 2, (c) No. 3, and (d) No. 4 simulated overlying rock samples.

3.2.1. Changes in Aromatic Hydrocarbons within the Overlying Rock

In the wavenumber range of 700–900 cm–1, the substitution vibration of aromatic hydrocarbons is dominant. After the diffraction pattern of the sample was fitted in this wavenumber range, absorption peaks at different positions are obtained, representing different vibration forms of substituted benzene, as shown in Figure . Their relative areas and assignments are shown in Table . There are five kinds of substitution on the aromatic ring, namely, monosubstitution benzene (700–730 cm–1), disubstitution benzene (730–750 cm–1), trisubstitution benzene (750–810 cm–1), tetrasubstitution benzene (810–850 cm–1), and pentasubstitution benzene (850–900 cm–1). As can be seen from Figure , a strong absorption peak exists at 880 cm–1 for each sample, which is the absorption peak of pentasubstituted benzene, and the concentration and migration range of such aromatic hydrocarbon in the simulated overlying rock is the highest.

6.

6

Open in a new tab

Fitting peak of infrared spectrum of No. 1, No. 2, No. 3, and No. 4 samples in the range of 700–900 cm–1: (a) 1–1, (b) 1–2, (c) 1–3, (d) 2–1, (e) 2–2, (f) 2–3, (g) 3–1, (h) 3–2, (i) 3–3, (j) 4–1, (k) 4–2, and (l) 4–3 sampling points.

2. Infrared Spectrum Diffraction Peaks and Attribution of No. 1, No. 2, No. 3, and No. 4 Samples in the Range of 700-900 cm–1 .
  1–1
 1–2
 1–3
 2–1
 2–2
 2–3
attribution center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/%
monosubstituted benzene 712 0.49 3.02 712 0.33 4.98 712 0.45 2.26 712 0.50 3.09 713 0.21 4.33 712 0.52 2.59
725 0.82 5.13 727 0.40 6.01 724 0.94 4.73 727 1.21 7.48 727 0.29 6.01 724 1.28 6.37
disubstituted benzene 750 1.83 11.42 / / / 741 1.61 8.12 / / / / / / 745 2.10 10.47
trisubstituted benzene 762 0.14 0.89 760 0.61 9.25 773 4.58 23.08 766 3.22 19.95 762 0.74 15.07 775 4.51 22.50
777 2.31 14.41 776 0.39 5.93 796 0.73 3.69 790 0.73 4.53 779 0.41 8.48 796 0.60 2.99
797 0.59 3.69 794 0.23 3.41 796 0.46 9.47
tetrasubstituted benzene 847 0.12 0.72 / / / 846 0.20 1.01 844 0.31 1.93 / / / / / /
pentasubstituted benzene 874 2.55 15.88 872 3.22 48.50 874 2.09 10.53 874 3.57 22.13 861 1.44 29.48 855 2.40 11.98
879 7.20 44.84 875 1.46 21.93 879 9.25 46.59 875 6.60 40.90 875 1.33 27.16 874 1.75 8.76
876 5.35 26.69
897 1.53 7.63
  3–1
 3–2
 3–3
 4–1
 4–2
 4–3
attribution center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/%
monosubstituted benzene 712 0.44 2.40 712 0.45 1.56 713 1.34 2.90 713 0.47 2.73 713 0.17 2.27 713 0.48 3.02
725 1.67 9.10 726 2.35 8.11 725 1.62 3.49 724 0.55 3.18 725 0.28 3.80 727 1.04 6.57
disubstituted benzene 743 1.46 7.97 741 0.75 2.59 746 5.02 10.82 748 2.05 11.86 750 1.42 19.51 742 0.30 1.89
trisubstituted benzene 759 1.51 8.25 758 3.72 12.86 764 2.82 6.07 774 2.85 16.56 777 1.50 20.56 762 3.88 24.45
776 3.89 21.23 778 4.59 15.88 780 5.32 11.47 794 0.77 4.45 796 0.35 4.86 785 1.65 10.36
796 0.94 5.13 797 1.25 4.33 797 1.65 3.55 799 0.51 3.22
tetrasubstituted benzene / / / / / / / / / / / / / / / / / /
pentasubstituted benzene 853 1.76 9.60 861 6.10 21.09 874 5.92 12.77 875 3.11 18.02 855 2.09 28.68 857 1.41 8.89
874 1.42 7.78 876 3.38 11.67 877 22.34 48.16 878 7.45 43.20 875 1.48 20.32 875 1.72 10.86
876 4.22 23.06 897 6.34 21.91 896 0.36 0.77 877 4.01 25.27
897 1.00 5.49 897 0.87 5.47
Open in a new tab

The types and relative contents of aromatic hydrocarbons in the 700–900 cm–1 interval at each sampling point of the simulated overlying rock are shown in Figure . It can be seen that the substitution form of benzene contaminants is mainly pentasubstituted benzene, with a relative content fluctuating around 60%, and even reaching 70% in some sampling points, which indicates that the main form of benzene contaminants generated by pyrolysis of bituminous coal is pentasubstituted benzene. The change in the relative content of pentasubstituted benzene is negatively correlated with that of trisubstituted benzene and disubstituted benzene, with the relative content of trisubstituted benzene fluctuating around 30% and reaching 40% only in sampling points 4–3, which may be related to the interconversion of benzene. The relative content of mono- and disubstituted benzene is low, mostly below 10%, with a slight fluctuation range. Tetrasubstituted benzene is very small or undetectable in all samples, possibly influenced by the test coal, which does not generate tetrasubstituted benzene, or the chemical bond of tetrasubstituted benzene is broken and decomposed to lower substituted forms during migration within the simulated overlying rock. In the four groups of samples, the relative contents of several substituted benzenes do not show large fluctuation patterns. Thus, it is inferred that these substituted benzenes’ migration abilities are approximately the same in short-distance migration. However, with the expansion of the migration range, the pentasubstituted benzene, which has a higher relative content, will migrate more than the other substituted forms of benzenes under the effect of the concentration gradient.

7.

7

Open in a new tab

Types and relative contents of aromatic hydrocarbons detected in (a) No. 1, (b) No. 2, (c) No. 3, and (d) No. 4 overlying rock samples.

3.2.2. Changes in Oxygen Functional Groups in Overlying Rocks

According to previous experience, − the absorption vibration zone of oxygen-containing functional groups is mainly in the range of 1000–1800 cm–1, which contains the stretching vibration of carboxyl, carbonyl, hydroxyl and ether bonds, as well as the bending vibration of methyl and methylene groups, the stretching vibration of CC in aromatic or condensed rings, and the absorption peaks of Si–O–Si and Si–O–C (ash). The partial contaminants generated by coal gasification and pyrolysis can be determined based on the absorption peaks in the wavenumber range of oxygen-containing functional groups. The stretching vibrations of alcohols, phenols, or ethers are mainly within the wavelength range 1000–1270 cm–1, and the stretching vibrations of aldehydes, ketones, or carboxylic acids are mainly within the wavelength range 1630–1755 cm–1. These two absorption peaks are used to judge contaminants. The fitted peaks of the FTIR diffraction pattern at 1000–1800 cm–1 for the simulated rock sampling points are shown in Figure . The attribution of the diffraction peaks and the relative contents of functional groups are shown in Table .

8.

8

Open in a new tab

Fitting peak of infrared spectrum of No. 1, No. 2, No. 3, and No. 4 samples in the range of 1000–1800 cm–1: (a) 1–1, (b) 1–2, (c) 1–3, (d) 2–1, (e) 2–2, (f) 2–3, (g) 3–1, (h) 3–2, (i) 3–3, (j) 4–1, (k) 4–2, and (l) 4–3 sampling points.

3. Infrared Spectrum Diffraction Peaks and Attribution of No. 1, No. 2, No. 3, and No. 4 Samples in the range of 1000–1800 cm–1 .
  1–1
 1–2
 1–3
 2–1
 2–2
 2–3
attribution center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/%
CO stretching vibration of alcohols, phenols, and ethers 1031 8.80 4.06 1014 34.39 18.74 1002 73.50 16.52 1044 15.63 5.19 1021 8.52 6.12 1027 44.99 18.25
1124 41.40 19.12 1127 77.46 42.22 1120 18.22 4.09 1085 97.85 32.50 1128 51.83 37.22 1110 16.05 6.51
1164 9.30 4.30 1158 10.18 2.29 1132 76.87 25.54 1149 38.12 15.46
1115 114.94 25.83
CO stretching vibration of aldehydes, ketones, and acids 1643 36.33 16.77 1679 9.19 5.01 1637 24.26 5.45 1668 4.92 1.63 1677 9.62 6.91 1691 7.19 2.92
  3–1
 3–2
 3–3
 4–1
 4–2
 4–3
attribution center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/% center/cm–1 area area/%
CO stretching vibration of alcohols, phenols, and ethers 1013 57.24 26.70 1018 70.77 33.52 1018 71.76 14.89 1024 49.29 18.61 1019 26.64 26.11 1025 44.67 19.37
1110 9.26 4.32 1111 5.40 2.56 1048 14.38 2.98 1110 19.06 7.19 1114 1.22 1.20 1113 21.41 9.28
1148 30.98 14.45 1129 87.13 41.27 1069 22.70 4.71 1149 40.70 15.36 1129 42.82 41.98 1154 27.42 11.89
1096 30.13 6.25
1121 7.37 1.53
1139 9.80 2.03
1151 93.49 19.40
CO stretching vibration of aldehydes, ketones, and acids 1695 3.95 1.84 1675 7.12 3.37 1677 10.04 2.08 1689 9.67 3.65 1675 6.39 6.26 1700 4.24 1.84
Open in a new tab

A summary of the relative content of oxygen-containing functional group absorption peaks in the four groups of simulated overlying rock sampling points is presented in Table and Figure . The graph shows that the oxygen-containing functional group contaminants generated by UCG are mainly alcohols, phenols, and ethers, with a relative content ranging from 30% to 70%, the primary substances causing groundwater pollution. The relative content of alcohols, phenols, and ethers at the sampling points in the middle of the four groups of simulated overlying rock shows an evident increase and then decrease at the top sampling point. The reason for this phenomenon may be the volatility of alcohols, phenols, and ethers, and these contaminants volatilize after stopping the gasification, resulting in less relative content detected at the bottom sampling points, and with the increase of migration distance, the overburden absorbs contaminants during migration, which attenuates their migration. Aldehydes, ketones, and acids are relatively low, basically below 10%.

9.

9

Open in a new tab

Variety and relative content change of oxygen-containing functional group contaminants in (a) No. 1, (b) No. 2, (c) No. 3, and (d) No. 4 overlying rock samples.

3.3. Analysis of the Migration Behavior of Inorganic Contaminants

The physical phase composition of samples was analyzed by using XRD tests, and the XRD diffraction pattern was compared with the standard phase cards in Jade for phase retrieval. The XRD diffraction patterns of four sets of simulated overlying rocks are shown in Figure . The X-ray diffraction patterns obtained from the XRD tests were subjected to background deduction using MDI Jade 6.0 analysis software. After smoothing and other operations, all phases in the sample can be obtained by comparing and analyzing with the standard spectrum of the International Data Center of the Powder Diffraction Federation. ,

10.

10

Open in a new tab

XRD diffraction pattern of (a) No. 1, (b) No. 2, (c) No. 3, and (d) No. 4 simulated overlying rock samples.

Among the inorganic substances causing groundwater pollution by UCG, the main ones are heavy metals, such as Pb, Cd, Mn, Co, Cr, V, Cu, Ni, and Zn. These heavy metals in coal are released with gasification and carried by coal gas, causing groundwater pollution and ultimately enriching animals, plants, and humans. Select Cd, Pb, Cr, Cu, and Mn with the highest toxicity for retrieval. To better reveal the migration behavior of heavy metals, 12 sampling points from the four samples were subjected to peak treatment, as shown in Figure .

11.

11

Open in a new tab

Diffraction peak of heavy-metal contaminants at the sampling point of (a) No. 1, (b) No. 2, (c) No. 3, and (d) No. 4 overlying rock.

  • (1)

    No. 1 simulated overlying rock.

    Compared with the bottom sampling points, the types of contaminants detected at the middle and upper sampling points of the simulated overlying rock have notably decreased. In the XRD diffraction patterns of three sampling points, PbBr2 and MnBr2 diffraction peaks are present, which may occur for two reasons, either due to the high content of Pb and Mn elements in the experimental coal or due to the strong migration ability of Pb and Mn. Among the three sampling points, Cr compounds were not detected based on the matching rate of the XRD pattern. As shown in the peak situation, CdBr2, PbBr2, CuBr2, CuBr, and MnBr2 were detected at 1–1 and 1–2. However, only PbBr2, CuBr2, and MnBr2 were detected at 1–3. Owing to the volatility, Cd in the upper sampling point of the simulated overlying rock may experience volatilization when exposed to air, so it cannot be detected in the XRD spectrum. Therefore, based on the XRD pattern analysis of the No. 1 simulated overlying rock, more residual Pb, Mn, and Cu were adsorbed in the simulated overlying rock sample, followed by Cd.

  • (2)

    No. 2 simulated overlying rock.

    In the physical phase retrieval of three sampling points in the No. 2 simulated overlying rock, the types of heavy-metal contaminants were significantly less than those in the No. 1 simulated overlying rock, which may be due to the porosity of the simulated overlying rock. The 2–1, located at the bottom, had more heavy-metal contaminants detected than the middle and upper sampling points due to its proximity to the gas inlet, with diffraction peaks of CuBr, PbBr2, and MnBr2. Only MnBr2 was detected at 2–2 and 2–3. Cr compounds were not detected in the No. 2 simulated overlying rock. Among the three sampling points, the distribution range of heavy metal Mn is more expansive, with the most robust migration ability among several analyzed heavy-metal elements, followed by Pb and Cu. From the three sampling points, as the migration range expands, the types of contaminants will decrease, indicating that the concentration of contaminants in the overlying rock will also decrease.

  • (3)

    No. 3 simulated overlying rock.

    Various heavy-metal contaminants were detected at sampling points of the No. 3 simulated overlying rock, but there were no diffraction peaks of Cr compounds. Almost all diffraction patterns of the samples exhibit diffraction peaks of MnBr2, PbBr2, and CuBr2, which are limited by the model size and indicate a more vital migration ability of these heavy-metal contaminants. Possibly affected by physical properties such as porosity, PbBr2 was not detected at 3–2 in the middle, possibly due to low element content or experimental errors.

  • (4)

    No. 4 simulated overlying rock.

In the sampling point of the No. 4 simulated overlying rock, only a relatively wide variety of heavy-metal contaminants were detected in the 4–1 at the bottom. The XRD pattern showed diffraction peaks of PbBr2, MnBr2, CuBr2, CuBr, and CdBr. Fewer contaminants were detected in the 4–2 and 4–3. The reason for the above situation may be that Pb, Mn, and Cu are enriched in the bottom sampling points due to the influence of the porosity of the simulated overlying rock. The content of Cd in the middle and upper sampling points is low, and there is also a volatilization phenomenon, so no diffraction peaks were detected in the XRD diffraction test.

3.4. Impact of Different Overburden Rocks on Contaminants Migration

The contaminants generated by UCG migrate with the gas through the cracks in the surrounding rock pores. Comparing the migration behavior of contaminants in the overlying rocks from No. 1 to No. 4, it was found that the migration ability of contaminants is influenced by porosity, and the content of heavy metal increases significantly with the increase of porosity. This is because as the particle size of sand and gravel in the porous medium increases, the porosity increases, thereby increasing the migration channel of contaminants and making it easier for heavy metals to migrate within the porous medium. However, the relative contents of benzene and oxygen-containing functional group contaminants did not show significant fluctuations in the four groups of samples. The migration ability of benzene and oxygen-containing functional group contaminants is approximately the same in short-distance migration. However, with the expansion of the migration range, the influence of porosity on the migration ability will increase. This also indicates that the overburden has a strong adsorption capacity for heavy metals and a weak capacity for benzene and oxygen-containing functional group contaminants.

To better control the migration of contaminants in the gasification process, the site selection of the gasifier should be considered. Compared with shallow coal seams, deep coal seams have significant advantages. , Sufficient burial depth ensures that the coal seam has an adequate distance from freshwater resources to minimize potential environmental pollution. Ultrahigh formation pressure will limit the pores and crack development of the overburden, and the impact of high temperature and combustion cavity on the overburden is much smaller than that of shallow coal seams. The contaminants carried by the gas are not easy to migrate due to the limitation of crack development of the overburden. Geological structure is an essential factor affecting the migration of contaminants. Faults easily become large-scale gas leakage points, which is extremely unfavorable to the control of contaminants. Construction of gasifiers in coal seams with many faults should be avoided. In the site selection of the gasifier, complete and unbroken surrounding rock should be selected as the overburden. Under the effect of high temperature, the mechanical properties of the surrounding rock will change. The surrounding rock with stable mechanical properties cannot easily produce contaminant migration channels, which is more conducive to controlling contaminant migration.

4. Conclusions

This work aims to study the migration behavior of contaminants generated within the dry distillation channels during UCG in the overburden. The conclusions are as follows:

  • (1)

    The main form of benzene contaminants entering the overburden after bituminous coal gasification is pentasubstituted benzene, and the relative content of pentasubstituted benzene was negatively correlated with that of trisubstituted benzene and disubstituted benzene.

  • (2)

    In the short-distance migration range, several substituted benzenes’ migration abilities are approximately the same. As the migration range expands, the pentasubstituted benzenes with higher relative content will have a more extensive migration range under the effect of concentration gradient than the other substituted benzenes.

  • (3)

    The oxygen-containing functional group contaminants generated by gasification are mainly alcohols, phenols, and ethers, which are volatile and have strong migration ability in overburden. They can migrate over long distances in overburden and are the main substances causing groundwater pollution.

  • (4)

    Among the inorganic heavy-metal contaminants generated by bituminous coal gasification, the migration ability of Mn is the greatest, followed by Pb, Cu, and Cd.

  • (5)

    The migration ability of contaminants is influenced by porosity. The larger the porosity, the stronger the migration ability and the more extensive the migration range of heavy metal. The migration ability of benzene and oxygen-containing functional group contaminants is approximately the same over short distances. However, as the migration range expands, the influence of porosity on their migration ability will increase.

  • (6)

    The types and concentrations of residual contaminants are highest in the overburden near the combustion cavity, and most of the contaminants will remain inside the overburden near the gasification coal seam during migration. The overburden has a significant adsorption effect on contaminants, which can effectively weaken their migration. The cracks in the overburden can cause large-scale migration of contaminants.

Acknowledgments

This study was financially supported by the National Natural Science Foundation of China (Nos. 52374211, 52304190, and 52304060) and the Shandong Natural Science Foundation (No. ZR2023QE117).

The authors declare no competing financial interest.

References

  1. Zeng N., Jiang K., Han P., Hausfather Z., Cao J., Kirk-Davidoff D., Ali S., Zhou S.. The Chinese Carbon-Neutral Goal: Challenges and Prospects. Adv. Atmos. Sci. 2022;39:1229–1238. doi: 10.1007/s00376-021-1313-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Yang D., Koukouzas N., Green M., Sheng Y.. Recent development on underground coal gasification and subsequent CO2 storage. J. Energy Inst. 2016;89:469–484. doi: 10.1016/j.joei.2015.05.004. [DOI] [Google Scholar]
  3. Liu Z., Deng Z., He G., Wang H., Zhang X., Lin J., Qi Y., Liang X.. Challenges and opportunities for carbon neutrality in China. Nat. Rev. Earth Environ. 2022;3:141–155. doi: 10.1038/s43017-021-00244-x. [DOI] [Google Scholar]
  4. Xi J., Liang J., Sheng X., Shi L., Li S.. Characteristics of lump lignite pyrolysis and the influence of temperature on lignite swelling in underground coal gasification. J. Anal. Appl. Pyrolysis. 2016;117:228–235. doi: 10.1016/j.jaap.2015.11.011. [DOI] [Google Scholar]
  5. Yang D., Sarhosis V., Sheng Y.. Thermal–mechanical modelling around the cavities of underground coal gasification. J. Energy Inst. 2014;87:321–329. doi: 10.1016/j.joei.2014.03.029. [DOI] [Google Scholar]
  6. Feng Y., Yang B., Hou Y., Duan T., Yang L., Wang Y.. Comparative environmental benefits of power generation from underground and surface coal gasification with carbon capture and storage. J. Cleaner Prod. 2021;310:127383. doi: 10.1016/j.jclepro.2021.127383. [DOI] [Google Scholar]
  7. Niu M., Wang R., Ma W., Guo W., Liu H., Liu S.. Methane formation mechanism during pressurized pyrolysis of coal core in the context of deep underground coal gasification. Fuel. 2022;324:124668. doi: 10.1016/j.fuel.2022.124668. [DOI] [Google Scholar]
  8. Li H., Zheng N., Guo G., Chen Y.. Control measures for reduction of arsenic and cadmium contamination during underground coal gasification without shaft. J. Cleaner Prod. 2019;219:960–970. doi: 10.1016/j.jclepro.2019.02.154. [DOI] [Google Scholar]
  9. Wu F., Huang S., Jiang Q., Jiang G.. Effects of pressure and heating rate on coal pyrolysis: A study in simulated underground coal gasification. J. Anal. Appl. Pyrolysis. 2023;175:106179. doi: 10.1016/j.jaap.2023.106179. [DOI] [Google Scholar]
  10. Eftekhari A. A., Van Der Kooi H., Bruining H.. Exergy analysis of underground coal gasification with simultaneous storage of carbon dioxide. Energy. 2012;45:729–745. doi: 10.1016/j.energy.2012.07.019. [DOI] [Google Scholar]
  11. Stańczyk K., Kapusta K., Wiatowski M., Świądrowski J., Smoliński A., Rogut J., Kotyrba A.. Experimental simulation of hard coal underground gasification for hydrogen production. Fuel. 2012;91:40–50. doi: 10.1016/j.fuel.2011.08.024. [DOI] [Google Scholar]
  12. Jiang L., Chen S., Chen Y., Chen Z., Sun F., Dong X., Wu K.. Underground coal gasification modelling in deep coal seams and its implications to carbon storage in a climate-conscious world. Fuel. 2023;332:126016. doi: 10.1016/j.fuel.2022.126016. [DOI] [Google Scholar]
  13. Su F.-Q., Yang J., He X., Dai M., Hamanaka A., Yu Y., Li W., Li J.. Influences of removable gas injection methods on the temperature field and gas composition of the underground coal gasification process. Fuel. 2024;363:130953. doi: 10.1016/j.fuel.2024.130953. [DOI] [Google Scholar]
  14. Zhang H., Xiao Y., Luo G., Fang C., Zou R., Zhang Y., Li X., Yao H.. Numerical simulation study on chemical ignition process of underground coal gasification. Energy. 2024;298:131350. doi: 10.1016/j.energy.2024.131350. [DOI] [Google Scholar]
  15. Wang C., Liu H., Zhang Y., Zou C., Anthony E. J.. Review of arsenic behavior during coal combustion: Volatilization, transformation, emission and removal technologies. Prog. Energy Combust. Sci. 2018;68:1–28. doi: 10.1016/j.pecs.2018.04.001. [DOI] [Google Scholar]
  16. Shen F., Liu J., Zhang Z., Dai J.. On-line analysis and kinetic behavior of arsenic release during coal combustion and pyrolysis. Environ. Sci. Technol. 2015;49:13716–13723. doi: 10.1021/acs.est.5b03626. [DOI] [PubMed] [Google Scholar]
  17. Strugała-Wilczek A., Kapusta K., Pankiewicz-Sperka M.. Pollutants release from the residues remaining after underground gasification (UCG) of ortho- and meta-lignites. Fuel. 2022;327:125126. doi: 10.1016/j.fuel.2022.125126. [DOI] [Google Scholar]
  18. Xu J., Gao W., Xie H., Dai J., Lv C., Li M.. Integrated tech-paradigm based innovative approach towards ecological coal mining. Energy. 2018;151:297–308. doi: 10.1016/j.energy.2018.02.090. [DOI] [Google Scholar]
  19. Chen F., Li H., Dai G., Guo G., Li W., Tang C., Zhou H., Liu C., Yuan Y., Tang L., Huo W., Liu X.. The new way for realizing carbon neutrality of coal and analysis of bearing characteristics and stability of coal pillar in production. J. Cleaner Prod. 2023;415:137766. doi: 10.1016/j.jclepro.2023.137766. [DOI] [Google Scholar]
  20. Feng M., Xin L., Wang Z., Li K., Wu J., Li J., Cheng W., Wang B.. Discussion on requirements of gasifier gas tightness for underground coal gasification production. Sustainable Energy Technol. Assess. 2021;47:101550. doi: 10.1016/j.seta.2021.101550. [DOI] [Google Scholar]
  21. Roddy D. J., Younger P. L.. Underground coal gasification with CCS: A pathway to decarbonising industry. Energy Environ. Sci. 2010;3:400–407. doi: 10.1039/b921197g. [DOI] [Google Scholar]
  22. Bhutto A. W., Bazmi A. A., Zahedi G.. Underground coal gasification: From fundamentals to applications. Prog. Energy Combust. Sci. 2013;39:189–214. doi: 10.1016/j.pecs.2012.09.004. [DOI] [Google Scholar]
  23. Shackley S., Mander S., Reiche A.. Public perceptions of underground coal gasification in the United Kingdom. Energy Policy. 2006;34:3423–3433. doi: 10.1016/j.enpol.2005.07.010. [DOI] [Google Scholar]
  24. Kapusta K., Stańczyk K., Wiatowski M., Checko J.. Environmental aspects of a field-scale underground coal gasification trial in a shallow coal seam at the Experimental Mine Barbara in Poland. Fuel. 2013;113:196–208. doi: 10.1016/j.fuel.2013.05.015. [DOI] [Google Scholar]
  25. Ütnü Y. E., Okutan H., Aydın A. A.. Polycyclic aromatic hydrocarbon (PAH) content of Malkara lignite and its ex-situ underground coal gasification (UCG) char residues. Fuel. 2020;275:117949. doi: 10.1016/j.fuel.2020.117949. [DOI] [Google Scholar]
  26. Pankiewicz-Sperka M., Stańczyk K., Płaza G. A., Kwaśniewska J., Nałęcz-Jawecki G.. Assessment of the chemical, microbiological and toxicological aspects of post-processing water from underground coal gasification. Ecotox. Environ. Safe. 2014;108:294–301. doi: 10.1016/j.ecoenv.2014.06.036. [DOI] [PubMed] [Google Scholar]
  27. Campbell J. H., Wang F. T., Mead S. W., Busby J. F.. Groundwater quality near an underground coal gasification experiment. J. Hydrol. 1979;44:241–266. doi: 10.1016/0022-1694(79)90134-3. [DOI] [Google Scholar]
  28. Strugała-Wilczek A., Stańczyk K.. Comparison of metal elution from cavern residue after underground coal gasification and from ash obtained during coal combustion. Fuel. 2015;158:733–743. doi: 10.1016/j.fuel.2015.06.009. [DOI] [Google Scholar]
  29. Kapusta K., Stańczyk K.. Pollution of water during underground coal gasification of hard coal and lignite. Fuel. 2011;90:1927–1934. doi: 10.1016/j.fuel.2010.11.025. [DOI] [Google Scholar]
  30. Kumabe K., Moritomi H., Ito W., Kambara S., Minowa T., Sakanishi K.. Material balances of major and trace elements in hydrogen production process from coal with CO2 recovery. Fuel. 2013;107:40–46. doi: 10.1016/j.fuel.2012.10.049. [DOI] [Google Scholar]
  31. Liu S., Wang Y., Yu L., Oakey J.. Volatilization of mercury, arsenic and selenium during underground coal gasification. Fuel. 2006;85:1550–1558. doi: 10.1016/j.fuel.2005.12.010. [DOI] [Google Scholar]
  32. Grabowski J., Korczak K., Tokarz A.. Aquatic risk assessment based on the results of research on mine waters as a part of a pilot underground coal gasification process. Process Saf. Environ. Protect. 2021;148:548–558. doi: 10.1016/j.psep.2020.10.003. [DOI] [Google Scholar]
  33. Dong M., Feng L., Zhou Q., Zhou S., Xu X., Qin B.. Spatial and temporal evolution of tar during ex-situ underground coal gasification. Fuel. 2022;317:123423. doi: 10.1016/j.fuel.2022.123423. [DOI] [Google Scholar]
  34. Sheng Y., Benderev A., Bukolska D., Eshiet K. I. -I., da Gama C. D., Gorka T., Green M., Hristov N., Katsimpardi I., Kempka T., Kortenski J., Koukouzas N., Nakaten N., Sarhosis V., Schlueter R., Torres V. N., Veríssimo A. C., Vesselinov V., Yang D.. Interdisciplinary studies on the technical and economic feasibility of deep underground coal gasification with CO2 storage in Bulgaria. Mitig. Adapt. Strateg. Glob. Change. 2016;21:595–627. doi: 10.1007/s11027-014-9592-1. [DOI] [Google Scholar]
  35. Soukup K., Hejtmánek V., Čapek P., Stanczyk K., Šolcová O.. Modeling of contaminant migration through porous media after underground coal gasification in shallow coal seam. Fuel Process. Technol. 2015;140:188–197. doi: 10.1016/j.fuproc.2015.08.033. [DOI] [Google Scholar]
  36. Ma X., Kang X., Wang Z., Wang X., Shi X.. Cl– Transport in Saturated Soils under Different Pore Conditions. Res. Explor. Lab. 2018;37:30–33. [Google Scholar]
  37. Krause D., Herdel P., Ströhle J., Epple B.. HTW-gasification of high volatile bituminous coal in a 500 kWth pilot plant. Fuel. 2019;250:306–314. doi: 10.1016/j.fuel.2019.04.014. [DOI] [Google Scholar]
  38. Wang Z., Liang D., Li Y., Tian H., Liang J.. Influence of scale and atmosphere on the pyrolysis properties of large-scale bituminous coal. J. Anal. Appl. Pyrolysis. 2021;158:105060. doi: 10.1016/j.jaap.2021.105060. [DOI] [Google Scholar]
  39. Xin L., Li C., Liu W., Xu M., Xie J., Han L., An M.. Change of sandstone microstructure and mineral transformation nearby UCG channel. Fuel Process. Technol. 2021;211:106575. doi: 10.1016/j.fuproc.2020.106575. [DOI] [Google Scholar]
  40. Chen Y., Mastalerz M., Schimmelmann A.. Characterization of chemical functional groups in macerals across different coal ranks via micro-FTIR spectroscopy. Int. J. Coal Geol. 2012;104:22–33. doi: 10.1016/j.coal.2012.09.001. [DOI] [Google Scholar]
  41. Xu M., Xin L., Liu W., Hu X., Cheng W., Li C., Wang Z.. Study on the physical properties of coal pyrolysis in underground coal gasification channel. Powder Technol. 2020;376:573–592. doi: 10.1016/j.powtec.2020.08.067. [DOI] [Google Scholar]
  42. Chen Y., Zou C., Mastalerz M., Hu S., Gasaway C., Tao X.. Applications of micro-Fourier transform infrared spectroscopy (FTIR) in the geological sciencesa review. Int. J. Mol. Sci. 2015;16:30223–30250. doi: 10.3390/ijms161226227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Xin L., An M., Feng M., Li K.. et al. Study on pyrolysis characteristics of lump coal in the context of underground coal gasification. Energy. 2021;237:121626. doi: 10.1016/j.energy.2021.121626. [DOI] [Google Scholar]
  44. Li B., Zhang W., Xie Z., Chen X., Cui Y.. FTIR and XRD microscopic characterisation of coal samples with different degrees of metamorphism. J. Mol. Struct. 2024;1309:138270. doi: 10.1016/j.molstruc.2024.138270. [DOI] [Google Scholar]
  45. Civiš S., Ferus M., Kubelík P., Jelinek P., Chernov V. E.. Potassium spectra in the 700–7000 cm–1 domain: Transitions involving f-, g-, and h-states. Astron. Astrophys. 2012;541:A125. doi: 10.1051/0004-6361/201218867. [DOI] [Google Scholar]
  46. Guillén M. D., Iglesias M. J., Domínguez A., Blanco C. G.. Fourier transform infrared study of coal tar pitches. Fuel. 1995;74:1595–1598. doi: 10.1016/0016-2361(95)00139-V. [DOI] [Google Scholar]
  47. He X., Liu X., Nie B., Song D.. FTIR and Raman spectroscopy characterization of functional groups in various rank coals. Fuel. 2017;206:555–563. doi: 10.1016/j.fuel.2017.05.101. [DOI] [Google Scholar]
  48. Dang H., Xu R., Zhang J., Wang M., Jia G., Wang Y., Duan W.. Investigation on co-combustion behavior and kinetic analysis of bamboo char/waste plastics (PVC) hydrochar. Thermochim. Acta. 2023;722:179466. doi: 10.1016/j.tca.2023.179466. [DOI] [Google Scholar]
  49. Zhou J., Liu G., Xu F., Wang S., Zhang H.. TG-FTIR and Py-GC/MS study of the pyrolysis mechanism and composition of volatiles from flash pyrolysis of PVC. J. Energy Inst. 2020;93:2362–2370. doi: 10.1016/j.joei.2020.07.009. [DOI] [Google Scholar]
  50. Zhang Y., Qi X., Zou J., Rao Y., Chen L., Zhang L., Ji Y., Liang Z.. Effects of water immersion on the pore structure and thermodynamic properties of coal gangue. Fuel. 2023;346:128273. doi: 10.1016/j.fuel.2023.128273. [DOI] [Google Scholar]
  51. Liu B., Zhang Y., Meng X., Chen J., Wang J., Wang X., Zhang Y.. Study on explosion characteristics of the inert substances at Longkou oil shale of China. Process Saf. Environ. Protect. 2020;136:324–333. doi: 10.1016/j.psep.2019.12.033. [DOI] [Google Scholar]
  52. Yuan L., Wang K., Zhao Q., Yang L., Wang G., Jiang M., Li L.. An overview of in situ remediation for groundwater co-contaminated with heavy metals and petroleum hydrocarbons. J. Environ. Manage. 2024;349:119342. doi: 10.1016/j.jenvman.2023.119342. [DOI] [PubMed] [Google Scholar]
  53. Pandey V. C., Singh J. S., Singh R. P., Singh N., Yunus M.. Arsenic hazards in coal fly ash and its fate in Indian scenario. Resour., Conserv. Recycl. 2011;55:819–835. doi: 10.1016/j.resconrec.2011.04.005. [DOI] [Google Scholar]
  54. Dahaghin Z., Mousavi H. Z., Sajjadi S. M.. Trace amounts of Cd­(II), Cu­(II) and Pb­(II) ions monitoring using Fe3O4@graphene oxide nanocomposite modified via 2-mercaptobenzothiazole as a novel and efficient nanosorbent. J. Mol. Liq. 2017;231:386–395. doi: 10.1016/j.molliq.2017.02.023. [DOI] [Google Scholar]
  55. Foroutan R., Peighambardoust S. J., Mohammadi R., Peighambardoust S. H., Ramavandi B.. Cadmium ion removal from aqueous media using banana peel biochar/Fe3O4/ZIF-67. Environ. Res. 2022;211:113020. doi: 10.1016/j.envres.2022.113020. [DOI] [PubMed] [Google Scholar]
  56. Nieć M., Sermet E., Chećko J., Górecki J.. Evaluation of coal resources for underground gasification in Poland. Selection of possible UCG sites. Fuel. 2017;208:193–202. doi: 10.1016/j.fuel.2017.06.087. [DOI] [Google Scholar]
  57. Jiang L., Chen Z., Farouq Ali S. M., Zhang J., Chen Y., Chen S.. Storing carbon dioxide in deep unmineable coal seams for centuries following underground coal gasification. J. Cleaner Prod. 2022;378:134565. doi: 10.1016/j.jclepro.2022.134565. [DOI] [Google Scholar]
  58. Bordeleau G., Lavoie D., Rivard C., Pinet N., Barton D., Hinds S., Al T.. Saline and hydrocarbon-bearing fluids detected in shallow aquifers of southern New Brunswick, Canada: Natural occurrence, or deep migration along faults and industrial wellbores? Sci. Total Environ. 2024;933:172999. doi: 10.1016/j.scitotenv.2024.172999. [DOI] [PubMed] [Google Scholar]
  59. Huang Z., Zeng W., Gu Q., Wu Y., Zhong W., Zhao K.. Investigations of variations in physical and mechanical properties of granite, sandstone, and marble after temperature and acid solution treatments. Constr. Build. Mater. 2021;307:124943. doi: 10.1016/j.conbuildmat.2021.124943. [DOI] [Google Scholar]

Articles from ACS Omega are provided here courtesy of American Chemical Society

RESOURCES