Assessment of calcium sulphate dihydrate on spontaneous 

combustion at Khwezela Colliery 

 

 

 

Thapelo Wilfred Ngoepe 

 

 

 

 

A research report was submitted to the Faculty of Engineering 

and the Built Environment, University of the Witwatersrand, 

Johannesburg, in partial fulfilment of the requirements for the 

degree of Master of Science in Engineering. 

 

 

 

 

Johannesburg, 2021 



i 

DECLARATION 

I declare that this report is my own, unaided work. I have read the University 

Policy on Plagiarism and hereby confirm that no plagiarism exists in this 

report. I also confirm that there is no copying, nor is there any copyright 

infringement. I willingly submit to any investigation in this regard by the 

School of Mining Engineering, and I undertake to abide by the decision of 

any such investigation. 

 

__________________________   17/10/2021 

Signature of Candidate    Date 

 

 

On this........17...........day of......................October........................................ 

.......2021...... (Year), at ........Wits University................................................  



ii 

ABSTRACT 

Coal spontaneous combustion (CSC) is a major concern in the exploitation 

and utilisation processes of coal. Various methods for prohibiting the 

spontaneous combustion of coal have been developed. This study aimed to 

determine the causes of spontaneous combustion of coal and assess the 

effectiveness of calcium sulphate dihydrate (gypsum) on spontaneous 

combustion at Khwezela Colliery in Mpumalanga, South Africa. 

In order to exploit coal at favourable costs at Khwezela Colliery, gypsum 

was applied to two drill holes and one coal stockpile affected by 

spontaneous combustion. Temperature changes of the three drill holes and 

coal stockpiles were measured daily for 21 days from 06h00 to 16h00. Data 

from the holes and stockpiles were represented graphically and analysed 

using one of the statistical techniques called t-test. Furthermore, a t-test of 

two samples assuming unequal variances was used, and the significance 

level of 0.05 was chosen. The test statistic critical value was 2.1 for the 

stockpiles and 2.0 for the holes. The absolute value of test statistics 

obtained from comparing the hot holes ranged from 0.0 to 1.7. At the same 

time, the absolute value of test statistics for comparisons of the same sides 

of the stockpiles ranged from 3.6 to 4.3. The treated stockpile produced an 

absolute value of test statistic of 2.0. 

The analysis has revealed that gypsum is effective in managing the 

spontaneous combustion of stockpiles. An increase in the concentration of 

gypsum resulted in a decrease in the spontaneous combustion of the 

treated stockpile. Similarly, an increase in the concentration of gypsum 

resulted in a decrease in the in-hole temperature fluctuation. The use of 

gypsum in managing spontaneous combustion results in a decrease in the 

operation costs, safety and productivity of mining operations affected by 

spontaneous combustion. 

 

 



iii 

ACKNOWLEDGEMENTS 

I would like to acknowledge the following: 

• Prof Bekir Genc (School of Mining Engineering, University of the 

Witwatersrand) for his passion to my research topic and patience 

through all phases of this research report. 

• Mr Mogodi Mahapa for motivating and supporting me during data 

collection. 

• Anglo American Coal for permitting me to use its’ site for performing 

the experiment. 

• University of the Witwatersrand for giving me an opportunity to enrol 

for Msc Mining Engineering. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



iv 

DEDICATION 

To my late Grandfather Thamaga Zacharia Ngoepe, my late uncles Kgotso 

David Ngoepe, and my late cousins Mpho and Kgaugelo Ngoepe for being 

there for me we were young. 

To my Grandmother Jeanette and my Mother Anna for supporting me 

financially and emotionally. 

To my Siblings Lerato and Tebogo for putting their trust in me. 

And the Almighty God (The Father, the Son and Holy Spirit). 

 

   !!Bakone Wee!! 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



v 

Contents 

DECLARATION ....................................................................................... i 

ABSTRACT............................................................................................. ii 

LIST OF FIGURES ................................................................................ xi 

LIST OF TABLES ................................................................................ xiv 

LIST OF EQUATIONS .......................................................................... xv 

LIST OF ABBREVIATIONS ................................................................. xvi 

1 INTRODUCTION ................................................................................ 1 

1.1 Background of the study .................................................................. 1 

1.2 Description of the study area ........................................................... 2 

1.3 Problem statement .......................................................................... 4 

1.4 Aims and objectives of the research ................................................ 5 

1.5 Justification for research.................................................................. 5 

1.6 Structure of the research report ....................................................... 6 

2 LITERATURE REVIEW ...................................................................... 8 

2.1 Introduction ...................................................................................... 8 

2.2 Definition of spontaneous combustion ............................................. 8 

2.3 Causes of spontaneous combustion ............................................... 8 

2.4 Factors affecting spontaneous combustion of coal ........................ 10 

2.4.1 Atmospheric effects on coal stockpile ......................................... 11 

2.4.2 Wind-driven forced convection and natural conduction ............... 12 



vi 

2.4.3 Influence of pyrite on spontaneous combustion of coal ............... 14 

2.5 Methods of predicting spontaneous combustion liability of coal .... 16 

2.5.1 Differential scanning calorimetry (DSC) method ......................... 17 

2.5.2 Thermogravimetric analysis (DGA) ............................................. 17 

2.5.3 Russian U index .......................................................................... 18 

2.5.4 Differential thermal analysis (DTA) .............................................. 19 

2.5.5 Crossing-point temperature (XPT) .............................................. 19 

2.5.6 Olpinski Index method ................................................................. 22 

2.5.7 Adiabatic calorimetry method ...................................................... 23 

2.6 Chemical inhibitors on spontaneous combustion of coal ............... 23 

2.7 Thermal decomposition of gypsum ................................................ 25 

2.7.1 Thermochemistry of gypsum ....................................................... 26 

2.7.2 Heat of dehydration ..................................................................... 27 

2.8 Summary ....................................................................................... 29 

3 RESEARCH METHODS .................................................................. 30 

3.1 Introduction .................................................................................... 30 

3.2 Sources of data ............................................................................. 30 

3.2.1 Data from the hot-holes ............................................................... 30 

3.2.2 Data from stockpiles .................................................................... 32 

3.3 Method of data collection............................................................... 34 

3.3.1 Data collection from hot-holes ..................................................... 34 

3.3.2 Data collection from stockpiles. ................................................... 35 

3.4 Method of data analysis................................................................. 35 

3.4.1 Data analysis of holes and stockpiles.......................................... 35 



vii 

3.5 Summary ....................................................................................... 37 

4 RESULTS AND DISCUSSION OF COAL STOCKPILES ................. 38 

4.1 Introduction .................................................................................... 38 

4.2 Stockpile temperature and atmospheric temperature .................... 38 

4.3 Interpretation of results .................................................................. 39 

4.3.1 Temperature measurement from the west side of the treated 

stockpile at 06h00 ....................................................................... 39 

4.3.2 Temperature measurements from the east side of the treated 

stockpile at 06h00 ....................................................................... 40 

4.3.3 Temperature measurements from the west side of the control 

stockpile at 06h00 ....................................................................... 40 

4.3.4 Temperature measurements from the east side of the control 

stockpile at 06h00 ....................................................................... 41 

4.3.5 Temperature measurement from the west side of the treated 

stockpile at 08h00 ....................................................................... 42 

4.3.6 Temperature measurements from the west side of the treated 

stockpile at 08h00 ....................................................................... 43 

4.3.7 Temperature measurements from the east side of the control 

stockpile at 08h00 ....................................................................... 44 

4.3.8 Temperature measurements from the west side of the control 

stockpile at 08h00 ....................................................................... 45 

4.3.9 Temperature measurements from the east side of the treated 

stockpile at 10h00 ....................................................................... 46 

4.3.10 Temperature measurements from the west side of the treated 

stockpile at 10h00 ................................................................... 47 

4.3.11 Temperature measurements from the east side of the control 

stockpile at 10h00 ................................................................... 48 



viii 

4.3.12 Temperature measurements from the west side of the control 

stockpile at 10h00 ................................................................... 49 

4.3.13 Temperature measurements from the east side of the treated 

stockpile at 12h00 ................................................................... 50 

4.3.14 Temperature measurements from the west side of the treated 

stockpile at 12h00 ................................................................... 51 

4.3.15 Temperature measurements from the east side of the control 

stockpile at 12h00 ................................................................... 52 

4.3.16 Temperature measurement from the west side of control 

stockpile at 12h00 ................................................................... 53 

4.3.17 Temperature measurements from the west side of the treated 

stockpile at 14h00 ................................................................... 54 

4.3.18 Temperature measurements from the west side of the control 

stockpile at 14h00 ................................................................... 55 

4.3.19 Temperature measurements from the west side of the control 

stockpile at 14h00 ................................................................... 56 

4.3.20 Temperature measurements from the east side of the control 

stockpile at 14h00 ................................................................... 57 

4.3.21 Temperature measurements from the west side of the treated 

stockpile at 16h00 ................................................................... 58 

4.3.22 Temperature measurements from the east side of the treated 

stockpile at 16h00 ................................................................... 59 

4.3.23 Temperature measurements from the west side of the control 

stockpile at 16h00 ................................................................... 60 

4.3.24 Temperature measurements from the east side of the control 

stockpile at 16h00 ................................................................... 61 

4.4 Comparison of same sides of the treated and control stockpiles ... 62 

4.4.1 West side temperature of the treated and control stockpiles 

variations at 06h00 ...................................................................... 62 



ix 

4.4.2 East side temperature variations of the treated and control 

stockpiles at 06h00...................................................................... 64 

4.4.3 West side temperature variations of the treated and control 

stockpiles at 08h00...................................................................... 66 

4.4.4 East side temperate variations of the treated and control stockpiles 

at 08h00 ...................................................................................... 68 

4.4.5 West side temperature variations of the treated and control 

stockpiles at 12h00...................................................................... 70 

4.4.6 East side temperature variations of the treated and control 

stockpiles at 10h00...................................................................... 72 

4.4.7 West side temperature variations of the treated and control 

stockpiles at 12h00...................................................................... 74 

4.4.8 East side temperature variations of the treated and control 

stockpiles at 12h00...................................................................... 76 

4.4.9 West side temperature variations of the treated and control 

stockpiles at 14H00 ..................................................................... 78 

4.4.10 East side temperature variation of the treated and control 

stockpiles at 14h00 ................................................................. 80 

4.4.11 West side temperature variations of the treated and control 

stockpiles at 16h00 ................................................................. 82 

4.4.12 East side temperature variations of the treated and control 

stockpiles at 16h00 ................................................................. 84 

4.5 Temperature variations of the treated stockpile. ............................ 86 

4.6 Description of the highest temperature on the control stockpile .... 88 

4.7 Summary ....................................................................................... 89 

5 RESULTS AND DISCUSSION OF IN-HOLE TEMPERATURE........ 91 

5.1 Introduction .................................................................................... 91 



x 

5.2 In-hole temperature variations ....................................................... 91 

5.3 Summary ....................................................................................... 96 

6 CONCLUSIONS AND RECOMMENDATIONS ................................ 97 

6.1 Conclusion ..................................................................................... 97 

6.2 Recommendation .......................................................................... 98 

6.3 Limitation of study and future research work ................................. 99 

7 REFERENCES ............................................................................... 100 

8 APPENDIX ..................................................................................... 110 

Appendix A: Khwezela Colliery spontaneous combustion ................. 110 

Appendix B: Control stockpile burning in day nine ............................. 111 

Appendix C: Control stockpile burned area ....................................... 111 

Appendix D: Temperature measurements of coal the stockpiles ........... 1 

Appendix E: Temperature measurements of coal the holes .................. 4 

 

 

 

 

 

 

 

 



xi 

LIST OF FIGURES 

Figure 1.1: Stratigraphic column for the Vryheid Formation in the Witbank 

Coalfields. (Hancox & Gotz, 2014) ...................................................... 3 

Figure 1.2: Stratigraphic column of the study area ..................................... 4 

Figure 2.1: Variation of the coal stockpile maximum temperature vs time 

for different wind speeds (Taraba & Michalec, 2014) ........................ 12 

Figure 2.2: contours of coal stockpile temperature at different stages of 

spontaneous combustion heating process (Taraba & Michalec, 2014)

 .......................................................................................................... 13 

Figure 2.3: Schematic of the Wits-Ehac apparatus setup (Wade, et al., 

1987) ................................................................................................ 22 

Figure 2.4: Differential analysis thermogram of coal sample (Wade, et al., 

1987) ................................................................................................ 22 

Figure 2.5: Enthalpies for gypsum products (Wakili, 2007) ...................... 28 

Figure 3.1 : Hot-hole with spraying machine ............................................ 30 

Figure 3.2 Type K-Thermocouple. (RS Thermocouple Selection Guide, 

2020) ................................................................................................ 32 

Figure 3.3 Treated coal stockpile with corresponding sides ..................... 33 

Figure 3.4 FLIR E85 thermal image ......................................................... 34 

Figure 4.1 S1W6 temperature trend ......................................................... 39 

Figure 4.2 S1E6 temperature trend .......................................................... 40 

Figure 4.3 S2W6 temperature trend ......................................................... 41 

Figure 4.4 S2E6 temperature trend .......................................................... 42 

Figure 4.5 S1W8 temperature trend ......................................................... 43 



xii 

Figure 4.6 S1E8 temperature trend .......................................................... 44 

Figure 4.7 S2W8 temperature trend ......................................................... 45 

Figure 4.8 S2E8 temperature trend .......................................................... 46 

Figure 4.9 S1W10 temperature trend ....................................................... 47 

Figure 4.10 S1E10 temperature trend ...................................................... 48 

Figure 4.11 S2W10 temperature trend ..................................................... 49 

Figure 4.12 S2E10 temperature trend ...................................................... 50 

Figure 4.13 S1W12 temperature trend ..................................................... 51 

Figure 4.14 S1E12 temperature trend ...................................................... 52 

Figure 4.15 S2W12 temperature trend ..................................................... 53 

Figure 4.16 S2E12 temperature trend ...................................................... 54 

Figure 4.17 S1W14 temperature trend ..................................................... 55 

Figure 4.18 S1E14 temperature trend ...................................................... 56 

Figure 4.19 S2W14 temperature trend ..................................................... 57 

Figure 4.20 S2E14 temperature trend ...................................................... 58 

Figure 4.21 S1W16 temperature trend ..................................................... 59 

Figure 4.22 S1E16 temperature trend ...................................................... 60 

Figure 4.23 S2W16 temperature trend ..................................................... 61 

Figure 4.24 S2E16 temperature trend ...................................................... 62 

Figure 4.25 west side temperature variation at 06h00 ............................. 63 

Figure 4.26 East side temperature variation at 06h00 ............................. 65 

Figure 4.27 West side temperature variation at 08h00 ............................ 67 

Figure 4.28 East side temperature variation at 08h00 ............................. 69 

Figure 4.29 West side temperature variation at 10h00 ............................ 71 



xiii 

Figure 4.30 East side temperature variation at 10h00 ............................. 73 

Figure 4.31 West side temperature variation at 12h00 ............................ 75 

Figure 4.32 East side temperature variation at 12h00 ............................. 77 

Figure 4.33 West side temperature variation at 14h00 ............................ 79 

Figure 4.34 East side temperature variation at 14h00 ............................. 81 

Figure 4.35 West side temperature variation at 16h00 ............................ 83 

Figure 4.36 East side temperature variation at 16h00 ............................. 85 

Figure 4.37 Temperature variations of treated stockpile .......................... 87 

Figure 4.38 Control stockpile highest temperatures ................................. 89 

Figure 5.1 In-hole temperature variations ................................................ 92 

Figure 8.1: Khwezela Colliery spontaneous combustion ........................ 110 

Figure 8.2: Control stockpile burning day 9 ............................................ 111 

Figure 8.3: Control stockpile burned ash ............................................... 111 

 

 

 

 

 

 

 

 

 

 

 



xiv 

LIST OF TABLES 

Table 3.1 t-test: Two samples assuming unequal variances .................... 36 

Table 4.2 t-test for east side at 06h00 ...................................................... 65 

Table 4.3 t-test for west side at 08h00 ..................................................... 67 

Table 4.4 t-test for east side at 08h00 ...................................................... 70 

Table 4.5 t-test for west side at 10h00 ..................................................... 71 

Table 4.6 t-test for east side at 10h00 ...................................................... 73 

Table 4.7 t-test for west side at 12h00 ..................................................... 75 

Table 4.8 t-test for east side at 12h00 ...................................................... 77 

Table 4.9 t-test for west side at 14h00 ..................................................... 79 

Table 4.10 t-test for east side at 14h00 .................................................... 81 

Table 4.11 t-test for west side at 16h00 ................................................... 83 

Table 4.12 t-test for east side at 16h00 .................................................... 85 

Table 4.13 t-test for treated stockpile ....................................................... 87 

Table 5.1 t-test for H1 and H3 .................................................................. 94 

Table 5.2 t-test for H2 and H3 .................................................................. 95 

Table 5.3 t-test for H1 and H2 .................................................................. 95 

 

 

 

 

 

 

 



xv 

LIST OF EQUATIONS 

Equation 2.1: Pyrite Oxidation.................................................................. 18 

Equation 2.2: Crossing Point Temperature .............................................. 20 

Equation 2.3: Wits-Ehac Index ................................................................. 21 

Equation 2.4: The Enthalpy ...................................................................... 25 

Equation 2.5: Heat Capacity .................................................................... 26 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



xvi 

LIST OF ABBREVIATIONS 

 

AEL  Africa Exploration Limited 

AHR  Average Heating Rate 

CSC  Coal Spontaneous Combustion 

DSC  Differential Scanning Calorimetry 

DTA  Differential Thermal Analysis 

FCC  Feng Chakravorty and Cochrae 

FT   Flammability Temperature 

LCD  Liquid Crystal Display 

ROM  Run Off Mine 

TCM/HR  Total cubic meters per hour 

TGA  Thermogravimetric Analysis 

WOP  Wet Oxidation Potential 

XPT  Crossing-Point Temperature 

XRF  X-Ray Fluorescent 

 

  



1 

1 INTRODUCTION 

The Khwezela Colliery lost thousands to millions of tonnes of coal due to spontaneous 

combustion. This loss included machines worth millions of Rands that caught fire in 

hot areas. Additionally, this resulted in low productivity of 2 200 tcm/h from the dragline 

compared to the target of 3 800 tcm/h target due to poor drilling and blasting from 

working in extremely hot areas. There have been incidents where holes filled with 

explosives have detonated prematurely, resulting in injuries. Thus, in order to mitigate 

the occurrence of premature detonation, mines have developed standard operating 

procedures. In addition, numerous researches are conducted to understand the 

mechanism of spontaneous combustion of coal (Onifade et al., 2020); for example, 

Hao et al. argue that the self-heating of coal occurs if the heat produced during 

oxidation exceeds the heat emitted to the environment (Hao, et al., 2013; Zhang, et 

al., 2016). Various chemicals have been tested to determine their ability to inhibit 

spontaneous combustion. For instance, Tsai et al. (2017) investigated and quantified 

the inhibition effects of Zn/Mg/Al-CO3 layered double hydroxide, thermo-sensitive 

hydrogel, di-ammonium phosphate, and sodium phosphate and magnesium chloride. 

The results demonstrated that Zn/Mg/Al–CO3 LDHs are extremely highly compatible 

with coal and form a crystalline structure on the surface of coal, which interrupts the 

diffusion of oxygen for combustion and, consequently, inhibits spontaneous coal 

combustion.   

1.1 Background of the study 

The chemistry of carbonaceous materials such as coal and coal shales make them 

undergo self-heating when exposed to atmospheric conditions; with an increase of 

pyrite content, the characteristic parameters of CSC decrease (Wen & Zhang, 2011). 

These characteristic parameters of coal include the release of CO, CO2 and CH4. The 

activation energy of coal decreases with increasing pyrite content; hence coal with a 

higher pyrite content tends to be more susceptible to spontaneous combustion 

(Fuqiang, 2019). The self-heating of coal shales which can start spontaneous 

combustion, has been reported in South African coalfields (Onifade & Genc, 2019a, b, 

c). Reactive sedimentary material has pores embedded in the solid together with the 

carbon-rich elements. This renders the rock porous to different fluids like water and air. 



2 

It also increases its surface area, thus making the organic particles reactive as it 

permits oxygen to get through (Dullien, 1979). 

Many researchers have focused more on the self-heating of coal, with few studies 

determining the self-heating of coal shales (Onifade, 2018). To expose coal, the coal 

shale material above coal, which often experiences spontaneous combustion, must be 

drilled, charged, blasted, and moved away. During charging, the extreme heat in the 

drill hole affects the explosives leading to premature detonation. In order to prevent 

premature detonation, the extreme heat in the drilled holes must be suppressed before 

and during charging. Multiple heat-suppressing products have been developed; 

however, not all have been tested successfully in mining operations. However, calcium 

sulphate dihydrate (gypsum) has been found to provide excellent fire protection 

because it dehydrates at temperatures around 1200C (Belmiloudi, 2005). Dehydration 

is an endothermic chemical reaction absorbing energy and thus acting as a barrier to 

heat transfer. It is the effectiveness of this barrier to suppress heat that is investigated 

in this research.  

1.2 Description of the study area 

Khwezela Colliery is a coal mine owned by Anglo American. It was formed as a result 

of the merger between Landau and Kleinkopje Collieries in 2016. It is situated in the 

South-Eastern part of eMalehleni in Mpumalanga Province, South Africa (Miningdata, 

2019). Khwezela Colliery coal area is in the Witbank. Witbank Coalfields has been the 

heart of coal mining in South Africa since the mining began in the early 1890s 

(Miningdata, 2019).  The initial mining method of coal was bord and pillar, usually with 

a very low coal recovery ratio of 45%, leaving a substantial amount of coal as pillars. 

The remaining pillars are currently being mined using the strip-mining method. 

Khwezela Colliery is situated in the Northern part of the Witbank Coalfields. The coal 

forms part of the Vryheid Formation of the Ecca group. Witbank Coalfields has coals 

with different characteristics, suitable for different applications, such as power 

generation, metallurgical, liquefaction, domestic and chemical sectors (Onifade, 2018). 

The Witbank Coalfields consists of five seams with a thick sedimentary sequence 

(shale, mudstone, sandstone, and siltstone), as shown in Figure 1.1. The seams are 

numbered from 1 to 5, following the order from the base upwards. 



3 

The 5-seam is 2m thick, 4-seam is 3m thick, 2-seam is 7m thick, and 1-seam is 2m 

thick. The 5-seam and 2-seam are previously mined using bord and pillar, while the 

other coal seams have not been mined previously. The 2-seam coal is intensely 

affected by spontaneous combustion, while the remaining coal seams are not affected 

by spontaneous combustion. 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 1.2 illustrates the stratigraphic column of the study area. The No.2 seam coal is 

approximately 7m thick and overlain by a combination of sandstone and siltstone 

together referred to as interburden. The interburden is predominantly grey in colour 

and is affected by spontaneous combustion as illustrated in Appendix A. the No.2 seam 

coal is underlain by a 1.35m thick 1 seam parting and 3m thick No.1 seam coal. The 

No.1 seam coal is underlain by a coarse grained and massive sandstone. 

Figure 1.1: Stratigraphic column for the Vryheid Formation in the Witbank Coalfields. 

(Hancox & Gotz, 2014) 



4 

 

 

 

 

 

 

 

 

1.3 Problem statement 

Khwezela Colliery has been experiencing spontaneous combustion since the opencast 

mining of 2-seam started in 1978. This has resulted in a loss of coal, the creation of 

excessive dust, noxious gases, burning of machines, premature explosives detonation, 

high maintenance costs, and loss of revenue. Based on the financial analysis of the 

mine, the colliery has incurred costs amounting to over 25% above the budget, which 

in most cases exceeded revenue as maintenance costs exceeded the budget. These 

problems were caused by spontaneous combustion, specifically during the drilling and 

blasting of hot holes.  

During the charging of blast holes, the temperature of the holes was measured for all 

the holes that were to be blasted. Any hole whose temperature was not more than 

800C was considered safe to be charged by the mine. Some of the holes were 

measured to have temperatures above 800C and could not be charged. This created 

Figure 1.2: Stratigraphic column of the study area 



5 

a large burden between the charged holes due to the wide scattering holes with unsafe 

temperatures across the drilled benches. Consequently, poor blasting fragmentation 

would be produced, resulting in low production of loading machinery.  

Blasted coal was observed to be burning, and it required to be sprayed with water 

before it was loaded to stockpile. This was done to reduce the temperature of the coal 

and avoid burning the loading and hauling machinery. In order to prevent this loss of 

coal, a chemical substance inhibiting spontaneous combustion was required. 

1.4 Aims and objectives of the research  

This research aimed to assess the effectiveness of gypsum in managing spontaneous 

combustion of blast holes and coal stockpiles at Khwezela Colliery. The following 

objectives were used to achieve the aim: 

• Investigate the causes of spontaneous combustion at Khwezela Colliery. 

• Assess the effectiveness of gypsum in managing temperature of the drill holes. 

• Assess the effectiveness of gypsum in managing the temperature of coal 

stockpiles affected by spontaneous combustion. 

1.5 Justification for research 

Numerous researches have focused on laboratory tests to determine the extent to 

which various chemical products suppress heat. While many of them yielded positive 

results, their application to the mining industry in hot holes has not produced 

satisfactory results. The inhibitors tested in hot holes have only proven effective in 

suppressing heat from the bottom of the hole. This was observed from the 

thermocouple reading before and after applying heat treatment products in hot holes 

at Khwezela Colliery and Tweefontein Colliery.  

Khwezela Colliery has experienced poor fragmentation resulting in poor dragline 

productivity and subsequently low coal exposure rates. This made it impossible to 

achieve the required targets of saleable coal products and loss of revenue. 

Additionally, there have been blasting incidents due to the premature detonation of 

explosives. The success of this research has helped to understand the effectiveness 

of gypsum to suppress spontaneous combustion of blast holes and coal stockpiles. 

Other mining operations experiencing hot holes will also benefit from the success of 

this research. 



6 

1.6 Structure of the research report 

This report consists of seven chapters which are structured as follows: 

Chapter 1: Introduction 

Chapter 1 placed into context the foundation on which this study is rooted. This was 

done by capturing the study's background, including some of the researchers' previous 

work. It also described the Khwezela Colliery in detail then formulated a clear and 

complete problem statement. The justification of the study was done by indicating 

specific reasons to conduct this study and the impact of the study. This chapter ended 

with the structure of the report to show a coherent and logical flow from one chapter to 

the next. 

Chapter 2: Literature review 

Chapter 2 explored and critically reviewed the past and present investigations on the 

mechanisms of spontaneous combustion, including factors that affect it. It then focused 

on gypsum, intending to describe how it is used and can be used, including the 

chemistry of gypsum. Controversial issues arising from different researchers are 

explored, and proposals are made on harmonising the different issues. 

Chapter 3: Research methods 

Chapter 3 described in detail the instruments and the methodology used for data 

collection. It also explained the statistical analysis done to assess the significance of 

gypsum in managing the spontaneous combustion of hot-holes and coal stockpiles. 

The use of 64-Channel, thermocouples, and FLIR thermal cameras to collect data was 

discussed in detail. The use of samples assuming unequal variance and the choice of 

0.05 significance level to assess gypsum is also explained in detail.                                                        

Chapter 4: Results and discussion on coal stockpile 

Chapter 4 showed the graphs of measurements taken daily for each side of the 

stockpile. It also described the observed pattern between the daily stockpile 

temperature and atmospheric temperature. The same sides of the stockpile were 

compared and discussed in order to describe meaningful relationships observed. 

Statistical analysis was also performed and discussed on the different sides and the 

same sides of the stockpiles. 



7 

Chapter 5: Results and discussion of in-hole temperature 

Chapter 5 showed the graphs used for the measurements taken on the hot holes. The 

effect of gypsum on the management of in-hole temperature was assessed and 

described in detail. Statistical analysis of data was also done to determine the 

effectiveness of gypsum in managing in-hole temperature. 

Chapter 6: Conclusion and recommendations 

Chapter 6 summarised the observed relationships between measurements of the 

stockpiles and hot holes. It also indicated the extent to which gypsum managed the 

temperature of the coal stockpiles and in-hole temperature. The limitations of the 

research were also outlined, including how research can be improved in future. 

Chapter 7: References 

Chapter 7 used the Harvard referencing style to indicate all the sources which were 

used in this study. 

  



8 

2 LITERATURE REVIEW 

2.1 Introduction 

This chapter defines what spontaneous combustion is and it probes into the various 

causes of spontaneous combustion. It also looks at various methods of predicting the 

spontaneous combustion liability of coal. The thermal decomposition of gypsum is 

reviewed in detail in terms of the thermochemistry of gypsum and the heat of 

dehydration. 

2.2 Definition of spontaneous combustion 

Genc & Cook (2015) reported spontaneous combustion risks in South African 

coalfields and the Witbank Coalfields of Mpumalanga Province in South Africa, and the 

mines which experience intense spontaneous combustion are Khwezela Colliery of 

Anglo-American Coal and Tweefontein opencast mine of Glencore. Other mines 

around the Witbank area are also experiencing spontaneous combustion. 

Spontaneous combustion of coal can occur when coal with relatively low ignition 

temperature begins to release heat. This occurs in several ways, either by oxidation in 

the presence of moisture and air; or by bacterial fermentation, which generates heat 

(Zang, et al., 2019). The generated heat is unable to escape resulting in an increase 

in the temperature of the coal. The temperature of the coal rises above the ignition 

point, thus causing spontaneous combustion. When the oxidiser such as oxygen and 

fuel are present in the required proportion in the reaction, the system experiences 

thermal runaway. 

2.3 Causes of spontaneous combustion 

Self-heating of coal and coal shales has been reported to be one of the causes of 

spontaneous combustion (Onifade & Genc, 2019a, b, c). In most of the coal mines in 

the Witbank area of Mpumalanga Province in South Africa, the burning of coal is easily 

observed. These include coal stockpiles, in-situ coal, coal shales above coal layers, 

especially in the previously mined-out coal seams, high walls and spoil heaps (Onifade, 

2018). All these coal constituents are known to be undergoing self-heating and 

distinguish large open-pit mines. These coal constituents, often containing uneconomic 

amounts of coal and other carbonaceous material, are exposed to the atmosphere for 

extended periods from which low-temperature oxidation can take place. Low-



9 

temperature oxidation occurs whenever carbon-containing material is exposed to 

oxygen in the air. The oxidation rate for a particular material depends on temperature, 

particle size, oxygen partial pressure, water content and extent of previous oxidation 

(Carras, 1994). The rate of this reaction increases exponentially with temperature. 

When the temperature increases sufficiently to be beyond the ignition temperature of 

the carbonaceous material, ignition starts which lead to spontaneous combustion. 

Numerous researches have focused on the spontaneous combustion of coal seams 

without looking at the spontaneous combustion of coal shales (Onifade & Genc, 2020). 

Spontaneous combustion of both coal seams and coal shales in the Witbank area has 

been extensively studied by Onifade & Genc (2018a, b, c). Aforementioned studies 

looked at 14 coals and 14 coal shales in the Witbank area. The study by Onifade & 

Genc (2018a, b, c) concluded that coal shales found in association with coal seams 

vary considerably in their intrinsic properties and spontaneous combustion liability 

(Onifade & Genc, 2019a, b, c; Onifade et al., 2019). From this observation, the study 

established the interrelationship between the spontaneous combustion liability and 

properties of coal and coal shales.  

Alpern & Lemos de Sousa (2002) stated that coal shale consists of 50% to 90% ash. 

This usually provides a clear indication of the coal quality. Coal and coal shales, 

consisting of varying proportions of organic matter and inorganic material, mainly 

crystalline, may undergo spontaneous combustion (Onifade & Genc, 2019a, b, c; 

Onifade, et al., 2019). This enables the rock to be porous to air, and with the increased 

surface area, the organic particles have reactive oxidation sides (Dullien, 1979). The 

implication is that oxygen will occupy the pores, increasing the likelihood of the organic 

material oxidation leading to spontaneous combustion. 

Coal shale may undergo spontaneous combustion due to the amount of pyrite, organic 

composition, reactive nature and coal rank (Onifade, et al., 2018). The effects of the 

intrinsic properties of coal shales such as ash content, moisture, volatiles, carbon, 

nitrogen, hydrogen, sulphur, and mineral composition causing the start of self-heating 

in coal is complicated and may be the reason for the difficulties in understanding the 

mechanisms of spontaneous combustion (Beamish & Hamilton, 2005). The 

spontaneous combustion liability of coal shales differs between bands of coal seams 

when exposed to oxygen in the air (Onifade & Genc, 2019a, b, c). 



10 

2.4 Factors affecting spontaneous combustion of coal 

Low-temperature oxidation of coal can be affected by several factors such as oxygen 

concentration, temperature, inherent moisture content, particle size and surface area 

(Zhang, 2001). It can also be affected by maceral composition, coal rank, volatile 

matter and chemical composition of coal (Scott, 2002). Eroglu (1992) supported by 

Onifade & Genc (2018), posited that spontaneous combustion could also be affected 

by coal's geological, environmental, mining, and physical and chemical composition. 

Phillips, et al. (2011) mentioned geological factors consisting of seam thickness, seam 

gradient, organic matter and geological discontinuities. Other factors which affect the 

spontaneous combustion of coal include ambient temperature, oxygen concentration, 

humidity, metamorphic grade, composition, moisture content, bulk density and particle 

size (Wang, et al., 2016). 

The mining of 2-seam using the strip-mining method often leaves the high-wall side of 

the strip exposed to air, thereby allowing the ingress of oxygen into the coal and coal 

shales to initiate spontaneous combustion (Onifade, 2018). At Khwezela Colliery, the 

coal left on benches and the cracks visible on the benches also affect spontaneous 

combustion (Onifade, 2018). Ozdeniz et al. (2015) classified air pressure, relative 

humidity, wind speed, wind direction, moisture and sun radiation as some of the 

environmental factors affecting spontaneous combustion. The presence of water on 

the 2-seam bords and the proximity to Olifant River could provide the moisture that 

exacerbates spontaneous combustion.  

Particle size and porosity of coal and coal shales affect the spontaneous combustion 

of coal, as illustrated by Mastalerz, et al. (2010) and supported by Onifade, et al. 

(2018). Coal with large particle sizes experiences lower spontaneous combustion 

liability than coal with a smaller range of particle distribution (Hansel, et al., 2004). 

Large particles have a smaller surface area and higher density, while smaller particles 

possess a bigger surface area and lower density. The liability of spontaneous 

combustion of coal was increased with decreasing particle size, increasing the 

moisture content of the coal, and decreasing air humidity (Kucuk, et al., 2003). This is 

evident after a 2-seam of Khwezela Colliery is mined and put on stockpile; it tends to 

undergo spontaneous combustion rapidly and intensely, as observed by the 

researcher. The 2-seam and 1-seam of Witbank Coalfields in South Africa have 



11 

different particle sizes and densities. The 1-seam has a higher granular and density 

than the 2-seam. The 1-seam at Khwezela Colliery is not affected by spontaneous 

combustion as it is not mined previously using board and pillar mining, while the 2-

seam is affected by spontaneous combustion as it was previously mined using the 

board and pillar mining method. This could be the reason for 2-seam to be adversely 

affected by spontaneous combustion, while 1-seam coal is not adversely affected by 

spontaneous combustion.  

Uludag (2007) explained that the extent of self-heating could be based on a complex 

relationship between various intrinsic and extrinsic factors of coal. Arisoy & Akgun 

(2000) found that the moisture content and oxygen in the air influence the spontaneous 

combustion liability of coal. Their studies are supported by Beamish & Hamilton (2005), 

who discovered that a low moisture content might support spontaneous combustion 

liability of coal while a high moisture content impedes spontaneous combustion liability 

of coal. This view agrees with the Khwezela Pit observation, where the areas observed 

to have reddish water accumulation are affected by spontaneous combustion, 

especially the lithology immediately above the water level. Khwezela Pit has high 

moisture due to the water observed on the No. 2 seam bords. This could be another 

reason for the No.2 seam being affected by spontaneous combustion. It is also 

observed that the moisture content of coal affects the initial stages of coal self-hearting 

(Ren, et al., 1999).  

2.4.1 Atmospheric effects on coal stockpile 

Self-heating of coal stockpiles poses a serious problem for both coal producers and 

users. Spontaneous ignition occurring in coal stores leads to the loss of precious coal 

resources and the emission of greenhouse and toxic gases (Carras & Young, 1994). 

Coal stockpiles are mainly studied in relation to recognizing basic variables affecting 

the process of self-heating (Zhu, et al., 2013). Thus, using mathematical models, the 

effects of coal characteristics such as reactivity or particle size, the effects of coal 

characteristics such as bed porosity, slope angle and stockpile height, as well as 

meteorological conditions such as solar radiation, oxygen concentration and wind 

speed on the self-heating of coal stockpiles were studied in more detail (Taraba & 

Michalec, 2014).  



12 

Figure 2.1 illustrates that the exposure of a coal stockpile to atmospheric winds 

reduces the safety margins. A wind speed of 1 m s−1 can be 

considered critical because when exceeded, temperature runaway occurs, and the 

spontaneous heating process in the stockpile begins to turn into uncontrolled 

combustion. The dynamics of self-heating are positioned between the curves of 

2 m s−1 and 3 m s−1, which corresponds well with the monthly average wind speed from 

the SW–NE direction of 2.35 m s−1. Obviously, concerning the progress of the 

spontaneous heating of the stockpile pile, the fluctuating character of the wind 

manifests itself by the average value of the wind speed from the prevailing direction 

(Taraba & Michalec, 2014). 

 

 

 

 

 

 

Air entering a stockpile play a more complex role. On the one hand, it cools the 

stockpile by taking away the generated heat, while on the other hand, the oxidation 

process becomes more intense. Both aspects immediately affect the development of 

the maximum temperature inside the stockpile, which is considered a key parameter 

characterising the risk of self-heating in coal stockpiles (Srinivasan & Pradeep, 1996). 

2.4.2 Wind-driven forced convection and natural conduction 

Stockpiles consisting of coarse and fine coal particles are affected by wind differently 

and to different extents, and different equations also govern them. Most of the 

investigations of coal stockpiles have focused on experimental methods of fine 

particles, which are about a few millimetres in diameter (Sipila & Auerkari, 2012). The 

gas flow within fine particles coal stockpile follows Darcy’s Law (Sipila & Auerkari, 

Figure 2.1: Variation of the coal stockpile maximum temperature vs time for different 

wind speeds (Taraba & Michalec, 2014) 



13 

2012). However, the diameters of coarse coals are much greater than those fine-

particle coals, ranging from 3cm to 20cm. This indicates that the gas flow within the 

coarse coal stockpile is inappropriate to be governed by Darcy’s Law because of the 

high Darcy’s parameter and Reynolds number. Coarse particles are more prone to 

spontaneous combustion than fine particles (Zhu, et al., 2013). 

 

Figure 2.2 illustrates Contours of temperature within the coal stockpile at different 

stages of the spontaneous combustion heating process when the wind blows with a 

speed of 3 m s−1. Hot spot temperature is of (a) 346 K; (b) 370 K; (c) 397 K; (d) 475 K. 

Numerical simulations with both fixed direction and real fluctuations of the airflow 

confirmed the promoting role of wind on the dynamics of the development of 

spontaneous heating as illustrated in Figure 2.2. Concerning progress in the 

spontaneous heating of the pile, the fluctuating character of the wind manifests itself 

by an average value of the wind speed from the prevailing direction. 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 2.2: contours of coal stockpile temperature at different stages of 

spontaneous combustion heating process (Taraba & Michalec, 

2014) 



14 

 

Wind-driven forced convection affects the gas flow within the stockpile greatly. 

Therefore, the temperature distribution of the coarse coal stockpile is influenced by 

wind velocity. On the one hand, with a wind blowing on the left side of a stockpile, there 

could be one hot spot in the coarse coal stockpile, and the temperature distribution is 

asymmetric. On the other hand, the self-ignition location in a coal stockpile moves 

towards the downstream and upper part of the coal stockpile when wind velocity 

increases. When the wind is gentle, the ignition occurs on the lower part of the coal 

stockpile, close to the surface of the windward side, which is consistent with the 

location of the hottest spot in a fine-particle coal stockpile (Akgun & Essenhigh, 2001). 

When the wind blows moderately at a velocity of 0.05m/s to 0.5m/s, the self-ignition 

takes place nearly on the centre of the stockpile, but with a wind velocity of 1m/s, the 

combustion location is at the upper part of the stockpile (Akgun & Essenhigh, 2001). 

2.4.3 Influence of pyrite on spontaneous combustion of coal 

The presence of sulphur in coal can be classified into organic and inorganic sulphur. 

Organic sulphur is hard to distinguish from other forms of sulphur due to its ability to 

combine with macromolecular structures in the form of covalent bonds with a complex 

structure (Beamish, et al., 2012). The inorganic sulphur in coal occurs in the form of 

pyrite and sulphate. Olivella, et al. (2002) quantified the sulphur content in coal seams 

to be between 0.3% to 15.1%. An excess amount of sulphur in coal promotes self-

heating, which lead to CSC. Hsieh & Wert (1985) measured the content of pyrite on 

lignite, sub bituminous, bituminous and anthracite coals of the United States of 

America to be from 0.59% up to 3.9%. Olivella, et al. (2002) measured the South 

African coal and some coal samples from around the globe to contain from 5.4% up to 

15.1% pyrite. The study of Waterberg Coal revealed coal as medium sulphur type coal 

with pyritic and organic sulphurs accounting for the bulk of the total sulphur (Makgato 

& Chirwa, 2017). Maceral analyses of coal showed that vitrinite is the dominant 

maceral (up to 51.8 vol. %), whereas inertinite, liptinite and reactive semifusinite 

occurred in proportions of 22.6 vol. %, 2.9 vol. % and 5.3 vol. % respectively. The ratio 

of fixed carbon to volatile matter, commonly referred to as fuel ration which indicates 

the combustion characteristics of the coal was determined.  



15 

Mastelerz (2010) indicated that pyrite as a major constituent of inorganic sulphur has 

significant influences on the spontaneous combustion liability of coal. Yang, et al. 

(2019) also noted that pyrite as an impurity is generally considered the main form of 

inorganic sulphur and has a notable impact on CSC. Pyrite reacts with oxygen in the 

presence of water to form hydro-peroxide (H2O2) and therefore initiates oxygen 

(Huffman & Huggins, 1985). Bhattacharya (1971) argues that pyrite with a 

concentration of 2% promotes the spontaneous combustion liability of coal. The type 

of pyrite within the coal determines whether rapid self-heating would occur (Beamish, 

et al., 2012), and coal consisting of high pyritic sulphur does not reach thermal runaway 

fast enough in a dry state compared to coal in a moist state.  

Arisoy & Beamish (2015) conducted an adiabatic oven test to measure the accelerating 

effect of pyrite and moisture on coal self-heating rates and reaction rate data for pyrite 

oxidation. This study found that coals of similar intrinsic spontaneous combustion 

reactivity can show quite dissimilar behaviours regarding the time taken to reach 

thermal runaway. In some circumstances, the moderating effect of moisture can delay 

thermal runaway considerably due to the heat loss from evaporation. Conversely, 

thermal runaway can be accelerated due to the presence of reactive pyrite. The pyrite 

reaction with oxygen also consumes moisture, which creates an additional drying effect 

that does not consume heat, unlike the normal moisture removal that takes place 

through evaporation. Consequently, the self-heating of the coal is accelerated, and a 

feedback mechanism develops that produces a dramatic self-heating behaviour not 

shown by previous studies (Arisoy & Beamish, 2015). 

Deng, et al. (2015) evaluated the effects of pyrite contents on one factor affecting the 

spontaneous combustion liability of coal. Coal samples with pyrite contents of 0%, 3%, 

5%, 7%, and 9% were produced by blending coal and pyrite. The DSC was used to 

determine the intensity of heat discharged during coal oxidation for the different pyrite 

contents. The study indicated that the presence of pyrite could accelerate the 

propensity of CSC. The DSC showed that the coal sample with a 7% pyrite content 

has the highest rate of heat flow. Samples with pyrite contents of 5% to 7% have the 

most significant influence on spontaneous combustion liability within the range of the 

study.  



16 

Sunjati & Zhang (1999) investigated the effect of inorganic matter on the spontaneous 

combustion behaviour of Victorian brown coal. Each of the fourteen samples they used 

was tested in an isothermal reactor to obtain its critical ambient temperatures with 

those of raw coal and the acid-washed coal. Potassium chloride, montan powder and 

sodium chloride were the most effective inhibitors, followed by magnesium acetate and 

calcium chloride.  The presence of sodium nitrate and ammonium chloride in the coal 

samples did not significantly influence spontaneous combustion. However, calcium 

carbonate, sodium acetate, potassium acetate, and pyrite promoted spontaneous 

combustion. The effect of additive loading was also investigated for an inhibition agent 

(KCl) and a promotion agent (NaAc). It was revealed that the effectiveness of these 

promotion and inhibition agents was enhanced with an increase in the additive loading. 

Low-temperature oxidation kinetics were also estimated by an energy balance 

approach and compared with the self-heating potential of these samples. The effects 

of reactor size and reactor specific surface area on the critical ambient temperatures 

are also discussed. 

A simultaneous thermal analysis experiment was likewise conducted by Yang, et al. 

(2019) to understand the influence of pyrite on the tendency of coal to undergo 

spontaneous combustion. This study found that with a higher pyrite content, 

characteristic parameters, the temperature corresponding to the maximum weight loss 

and peak temperatures of coal samples are lowered. They concluded that the 

activation energy of coal samples decreases with increasing pyrite content. Coal with 

high pyrite content tends to be more liable to spontaneous combustion. All the 

investigations found that pyrite promoted the spontaneous combustion of coal. Lain 

(2009) expressed the pyrite oxidation as illustrated in Equation 2.1: 

Fe2S + 7O2 + 16H2O =  2HsSO4 +  2FeSO4. 7H2O + 1321KJ (2.1) 

The equation above is an exothermic reaction that occurs at low temperatures, which 

generate heat that is double that of coal with the same oxygen (Martinez, 2009). This 

indicates that the presence of pyrite is a contributing factor towards the spontaneous 

combustion liability of coal.  

2.5 Methods of predicting spontaneous combustion liability of coal 

There is currently no specific standard method of evaluating spontaneous combustion 

liability of coal due to the inherent variability of coal properties. Various organizations 



17 

have used various techniques to evaluate the spontaneous combustion liability of coal. 

A brief description of the methods to predict spontaneous combustion of coal are 

discussed: 

2.5.1 Differential scanning calorimetry (DSC) method 

This method determines the changes in energy inputs provided to a substance and a 

reference material as a function of temperature when both materials are kept at a 

controlled temperature. Sahu, et al. (2004) used DSC to evaluate the spontaneous 

combustion liability of coal. Thirty coal samples from seven different Indian Coalfields 

were investigated and their initial temperature determined. The study indicated that an 

increase in the temperature indicates the spontaneous combustion liability of coal. 

Zhang, et al. (2016) used the DSC to determine the intrinsic reaction of Ximeng brown 

coal oxidation at low temperatures.  The heat evolution of the intrinsic reaction after 

eliminating the water evaporation and thermal decompositions of the inner oxygen-

containing functional groups was obtained by subtracting the DSC curve in N2 from the 

DSC curve in the air. It is considered that the intrinsic reactions between coal and 

oxygen could be divided into three stages, including the slow oxidation, accelerated 

oxidation and rapid oxidation stages. Compared with the DSC-air curve, the DSC-sub 

curve based on the subtracting results elucidated the exothermic characteristics of an 

intrinsic oxidation reaction in each stage more clearly. In addition, the DSC-sub curve 

reduced the experimental errors inborn from the heating rate and the sample mass, so 

it had a more practical application value than DSC-air curves. Activation energies 

obtained from DSC-sub curves can better reflect intrinsic oxidation reaction and be 

used as important indicators for the evaluation of CSC (Zhengfeng, et al., 2016).  

2.5.2 Thermogravimetric analysis (DGA) 

This method estimates the loss in weight of coal samples at variable temperatures due 

to self-heating. A specific coal sample is heated through a programmed heating 

process and plotted against the time/temperature. The results are termed 

Thermogravimetric (TG) curves. The created TG curve is referred to as the differential 

Thermogravimetric (DTG) curve and is the difference between the coal curve and the 

inert material curve. Choudhury et al. (2007) and Onifade et al. (2020) used the TGA 

technique to assess spontaneous combustion characteristics of different coal samples. 

Choudhury, et al. (2007) found that the amount of vitrinite and lipnite showed high 



18 

spontaneous combustion liability. The parameters used in the method were observed 

to have a strong relationship with the petrographic composition that combines the 

effect of coal rank and mineral matter (Choudhury, et al., 2007). 

Chen, et al. (2019) used Thermogravimetric (TGA) and in-situ Fourier transform 

infrared spectroscopy to study spontaneous combustion in bituminous coal. The 

results show that the coal’s spontaneous combustion can be divided into five stages. 

The spontaneous combustion of Gubei bituminous coal (Chen, et al., 2019) is divided 

into five stages. Stage I is the water evaporation and minimal mass loss stage (30 °C–

135.7 °C), Stage II is the oxygen absorption weight increase stage (135.7 °C–

294.6 °C), Stage III is the slow chemical reaction stage (294.6 °C–419.5 °C), Stage IV 

is the combustion stage (419.5 °C–574.3 °C), and Stage V is the burnout stage 

(temperatures > 574.3 °C).  

2.5.3  Russian U index 

This method estimates the amount of oxygen absorbed by individual coal samples over 

24 hours (Banerjee, 2000).  The gases obtained under the experimental conditions 

may be quantified by evaluating gas composition. The oxygen absorbed during the 

testing is directly proportional to the spontaneous combustion liability of coal (Banerjee, 

2000). The problem with this method is that the volume of oxygen absorbed by the coal 

sample during testing is not reproducible when repeated with the same coal. 

Panigrahi, et al. (1997) studied and presented the experimental setup for determination 

of the Russian U index. Ten coal samples from Jharia coalfield have been analysed 

using this method. The carbon, hydrogen, nitrogen and sulphur contents for these 

samples were determined using Fenton`s method of ultimate analysis modified at the 

Central Fuel Research Institute, Dhanbad, India. In addition to this, the XPT of these 

samples were also determined. Attempts were made to correlate the Russian U index 

and XPT of coal samples with its basic constituents, viz., carbon, and hydrogen and 

ash contents. It was also observed that from the point of susceptibility of spontaneous 

combustion the Russian U index shows a similar relationship with the basic 

constituents of coal as that of the crossing point temperature. (Panigrahi, et al., 1997) 



19 

2.5.4 Differential thermal analysis (DTA) 

This method involves heating a small coal sample at a constant temperature and 

keeping records of the temperature difference within the material and similar inert 

material as a function of temperature existing in the medium. This indicates the 

changes in a material's chemical and physical properties at the particular temperature 

and the properties of the material used (Mohalik, et al., 2010). Uludag (2007) used this 

method to study the spontaneous combustion liability of South African coals with a 

small-scale laboratory testing apparatus. Each sample tested for the analysis has 

different characteristics in terms of calorific value, volatiles, moisture content, and 

porosity. It is impossible to isolate a single property of coal and analyse it individually. 

DTA analysis results are a combined effect of the inherent characteristics of coal. A 

certain sequence of events occurs during the heating process, which can be analysed 

using various regions of the DTA thermogram. The first stage of the heating process 

involves oxygen absorption and loss of inherent moisture. This is evident from the 

decline of temperature and the slope of the curve. The DTA curve rapidly accelerates 

during the second stage due to volatiles. Since most of the moisture is lost during the 

first stage, no temperature decrease is observed in the second stage. The volatiles 

and the constant increase in coal temperature catalyse the self-heating process, 

occurring at temperatures around 70–90°C. This minimum point is believed to be one 

of the most important aspects of the DTA curve. Therefore, a more detailed analysis 

of DTA should be used when describing the behaviour of coal in a standard testing 

environment. The Wits-Ehac Index should be modified to include the minimum point of 

acceleration and inherent moisture content as factors in self-heating (Uludag, 2007). 

Nimaje & Tripathy (2016) used DTA to assess the liability of some Indian coals to 

spontaneous combustion. Their studies found that the flammability temperature, Wet 

oxidation potential, and DTA studies used to assess the spontaneous combustibility 

character indicated no significant correlation with the intrinsic properties (Nimaje & 

Tripathy, 2016). 

2.5.5 Crossing-point temperature (XPT) 

The experimental tests of this method involve heating coal in an oxidised condition to 

cause low-temperature oxidation either at an automatic heating rate or at a certain 

temperature from the ambient temperature to the ignition temperature of the coal 



20 

(Onifade, 2018). This method is extensively used in South Africa, Poland, Turkey and 

India to categorize spontaneous combustion liability of different coal seams. Coal with 

a lower liability index has a higher XPT. Humphreys (1979) argues that this method is 

not suitable because it does not consider the inherent properties of coal and the design 

of the experiment. Issues have been raised on the crossing-point temperature (CPT) 

techniques due to the variation in the setting of a reference point, which is partly 

reflected in the disputes among the developers of the individual techniques (Wang, et 

al., 2011). As reported in the literature (Chen, 1999), the CPT determined by Chen’s 

technique departs from the oven temperature, with a variation ranging from several to 

a few tens of kelvin. The extent of departure depends on the temperature of the oven 

and the properties of the sample tested. These two techniques are almost identical in 

nature but yield different test results even under the same experimental conditions. 

The obvious question is which results are more reliable. Generally speaking, in the 

utilisation of the CPT techniques, there are two basic impending issues:  

1. How does the temperature of the crossing-point and its corresponding rate of 

temperature rise relate to the kinetics of the exothermic reactions? 

2.  How do the crossing-point temperatures measured contain essential information 

for reliable determination of the kinetic parameters associated with the reactivity of 

solids? 

Chen (1999) answers the above questions by saying that the CPT, where the heat 

conduction diminishes at the centre of a symmetrical exothermically reactive solid, can 

be considerably different from the set oven temperature during a transient basket 

heating procedure for measuring exothermic reactivity. The CPT differs from the oven 

temperature by a larger amount for a greater oven temperature and depends on 

sample size and the nature of the materials concerned. Such differences can, under 

certain circumstances, lead to considerable variations in the estimation of the kinetic 

parameters for the two existing transient testing procedures. This is an important point 

of consideration for future work in the area of thermal ignition of particulate materials. 

Barve & Mahadevan (1994) have shown the relationship of the inherent properties of 

coal to XPT as illustrated in Equation 2.2: 

XPT = 168.8 − 10.3M + 0.12A + 0.69M2 − 0.06MA + 0.01A2 (2.2) 

                                             



21 

where M is the moisture content, A is the ash content. 

The XPT and DTA of selected coal samples have been used jointly to obtain a 

consistent self-heating liability index, the Wits-Ehac Index (Onifade, 2018). The Wits-

Ehac Index was developed in South Africa in the late 1980s to test the spontaneous 

combustion liability of coal (Eroglu, 1992). The apparatus consists of an oil bath, three 

coal and inert materials, an oil circular, a heater, a flowmeter, an air supply compressor 

and computers illustrated in Figure 2.1 (Wade, et al., 1987).   When using the DTA, the 

difference in temperatures between the coal sample and an inert material sample is 

measured by a data logger, stored in a computer, and plotted against the temperature 

of the inert material sample. When the temperature difference between the inert 

material and the coal sample is plotted against the inert temperature, the part of the 

graph where the coal is heating faster than the inert sample is termed Stage II.  

It is important to understand that during the DTA, three stages are obtainable. During 

Stage I, the temperature of an inert material sample is higher than the temperature of 

the coal sample. During Stage II, the coal sample begins to heat up at a higher rate 

than the heating rate of the inert material. High exothermicity is reached when the line 

crosses the zero-base line and is referred to as the XPT. The index makes use of the 

fact that coal highly prone to self-heating has a steeper Stage II slope and a lower XPT 

than coal not highly prone to self-heating. According to Wade et al. (1987), coal with a 

spontaneous combustion liability index below 3 is low risk, 3 to 5 medium risk, and coal 

with values greater than 5 are high risk. The index is calculated from the formula in 

Equation 2.3. The thermogram in Figure 2.2 illustrates the stages and the XPT for a 

given coal sample. 

 

Wits − Ehac Index = (
Stage II slope

XPT
) ∗ 500 (2.3) 

   

 

   



22 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2.5.6 Olpinski Index method 

In this method, a pellet of powdered coal of 0.4g is heated at a constant rate in a 

Quinone steam bath with the flow of air through the pulverised coal. The time against 

the temperature curve is recorded until a temperature of 2350C is reached. The 

temperature increase of the coal at this stage is used to provide a better definition of 

the spontaneous combustion liability index of Indian coal by establishing the 

Figure 2.3: Schematic of the Wits-Ehac apparatus setup (Wade, et al., 1987) 

Figure 2.4: Differential analysis thermogram of coal sample (Wade, et al., 1987) 



23 

relationship between XPT, FT, WOP, proximate and ultimate analysis (Nimaje & 

Tripathy, 2016). This technique is generally used in Poland to categorize the 

spontaneous combustion liability of coal. The liability index is referred to as Szb Index. 

2.5.7 Adiabatic calorimetry method 

This technique involves placing a coal sample in a reaction vessel either in an adiabatic 

oven or oil bath such that the heat is not dissipated from the vessel. The coal 

temperature in a reaction vessel is controlled at intervals relative to the increase in the 

coal temperature. The reacting air or oxygen flows through the reaction vessel. This 

method is used in South Africa and New Zealand to reproduce the original condition of 

self-heating characteristics (Cliff, et al., 1996). The rate of temperature increases, and 

ignition temperature and the kinetic constant of coal are used to determine the 

proneness of coal to spontaneous combustion. Chen, et al. (2016) Use of adiabatic 

calorimetry to characterise thermal runaway of Li-ion cells is a crucial technique in 

battery safety testing. Various states of charge (SoC) of Li-ion cells were investigated 

to ascertain their thermal runaway features using a Vent Sizing Package 2 (VSP2) 

adiabatic calorimeter. To evaluate the thermal runaway characteristics, the 

temperature-pressure-time trajectories of commercial cylindrical cells were tested, and 

it was found that cells at a SoC of greater than 50% were subject to thermal explosion 

at elevated temperatures. Calorimetry data from various 18650 Li-ion cells with 

different SoC were used to calculate the thermal explosion energies and chemical 

kinetics; furthermore, a novel self-heating model based on a pseudo-zero-order 

reaction that follows the Arrhenius equation was found to be applicable for studying 

the exothermic reaction of a charged cell (Chen, et al., 2016). Having determined the 

various methods of predicting CSC, the various chemicals which have the potential to 

inhibit CSC are necessary to be investigated. 

2.6 Chemical inhibitors on spontaneous combustion of coal 

Many theories have been developed to explain the mechanism of CSC since the 17th 

century (Stach, et al., 1982). These theories include pyrite and phenolic action 

theories, coal-oxygen reaction theory, bacteria action theory, free radical theory, 

hydrogen atom theory and group action theory. Amongst all the proposed theories, the 

coal-oxygen reaction theory seems to have obtained the approval of most scholars (Li, 

et al., 2020). Experimental investigations confirm that coal adsorbs oxygen and an 

https://www.sciencedirect.com/topics/engineering/thermal-explosion
https://www.sciencedirect.com/topics/engineering/calorimeter
https://www.sciencedirect.com/topics/engineering/system-on-chip
https://www.sciencedirect.com/topics/engineering/arrhenius-equation
https://www.sciencedirect.com/topics/engineering/exothermic-reaction


24 

oxidation reaction occurs between coal and oxygen. This interaction causes gradual 

heat accumulation, creating favourable conditions for spontaneous combustion (Xiao 

et al., 2018).  

Physical-based materials for retarding CSC, such as chlorine salts (MgCl2, KCl, CaCl2, 

and NaCl), have been used (Wang & Dou, 2014). These materials can retain water 

due to their hydrophobic properties. After they have absorbed water, a liquid 

membrane forms on the coal, preventing oxygen from coming into contact with the 

coal. The inhibition efficiency of 88% can be achieved using chlorine salts.  

Sujiganti & Zhang (2000) analysed the effects of additives on the critical ambient 

temperature above which thermal runaway occurred and analysed the reaction rate of 

acid-washed coal. They explained that the effects of additives on CSC depended on 

the anion and cation in them. CaCl2 and NaCl enhanced the critical ambient 

temperature and decreased the reaction rate, presenting an inhibition performance on 

the CSC. Zhang (2010) selected 20% MgCl2 as an inhibitor to treat CSC and found 

that CO (Carbon Monoxide) production during oxidation was significantly suppressed. 

Ammonium salts such as NH4Cl, NH4H2PO4, (NH4)2HPO4, and NH4HCO3 are 

commonly used CSC inhibitors. Ammonium salts exhibit a high water retention 

capacity (Li et al., 2020). These materials easily undergo thermal decomposition, which 

is an endothermic process, and the heat generated from coal oxidation is absorbed. 

Moreover, the pyrolysis products of ammonia (NH3) and Carbon dioxide (CO2) can 

dilute the concentration of oxygen (Zheng, 2010).  

The acid products of ammonium salts such as H3PO4 can rupture hydroxyl groups of 

coal to limit spontaneous combustion (Liodakis, et al., 2002). Su, et al. (2014) reported 

that NH4H2PO4, the main material used for developing ABC (mono ammonium 

phosphate-based) powders, underwent thermal decomposition when heated. This 

action may suppress heat accumulation in the process of CSC. Zeng, et al. (2010) 

used 20% NH4HCO3 and 20% NH4H2PO4 as inhibitors to investigate their potential 

inhibition on CSC. Their studies reported a CSC inhibition rate of 74% to 80%. 

However, poor thermal stability limited the application of ammonium salts as a 

spontaneous combustion inhibitor. Moreover, the pyrolysis product of NH3 is a toxic 

gas and is a health hazard for mine-workers.  



25 

The oxidation process causes an expansion for the volume of pyrite, thus promoting 

the development of coal pores. This exposes coal to oxygen, thereby promoting a coal-

oxygen reaction. Yang (1996) simulated the oxidation process of coal by hydrogen 

peroxide and found that 10%-15% Ca (OH)2 solution provides considerable 

performance in inhibiting high-sulphur coal oxidation. Ca(OH)2 mainly inhibited 

spontaneous combustion in two ways. Ca(OH)2 disrupted the self-oxidation cycle of 

pyrite, and the CaSO4 generated in the reaction had low water solubility. This CaSO4 

settled on the surface of coal to form a hydrophilic membrane. Furthermore, the 

colloidal substance Fe(OH)3 generated in the reaction encapsulated the coal by 

forming a protective coating that isolated oxygen from coal, thereby inhibiting the 

oxidation reaction. The inhibition performance of Ca(OH)2 is relatively stable; however, 

low solubility can cause blockage in the device. 

Inert gases and foams, mainly N2 and CO2, are generally used to forestall spontaneous 

combustion (Banerjee, 2000). When pumped into an enclosed area, the inert gases 

dilute the oxygen concentration in the space, thus inhibiting the coal oxidation (Shi & 

Zhou, 2014). Smith (1980) investigated the mechanism of CO2 for the heat treatment 

of coal stockpiles and found that CO2 reduced the rate of oxidation and inhibited 

spontaneous combustion.  Ren, et al. (2019) also examined the effect of adding N2 

and CO2 on spontaneous combustion and found that CO2 has better inhibitory 

performance than N2. Liquid N2 and liquid CO2 are potentially more efficient heat 

transfer mediums due to a considerable amount of heat being absorbed when liquid 

vaporises (Ray & Singh, 2007). This vaporization leads to an expansion in the volume 

of the cryogenic material, which results in an isotropic allocation of the heat-absorbing 

gas, thereby forcing the hot combustion gases out and displacing oxygen completely 

(Kim, 2004). Gases flow easily and cannot be trapped inside the danger area for a long 

period. Foam materials such as three-phase foam have been developed to restrict inert 

gases (Li, et al., 2020). Gypsum has not been tested on CSC, although it has promising 

application on the CSC. 

2.7 Thermal decomposition of gypsum 

Gypsum is used in building materials due to its excellent fire protection abilities (Wakili, 

2007). The main property of gypsum to inhibit is due to its dehydration at elevated 

temperatures. Dehydration is an endothermic chemical reaction that absorbs energy 



26 

hence acting as a barrier to heat transfer. During the dehydration process, the water 

of crystallisation is transformed to vapour and released. This vapour is released by 

pressure through the pores of gypsum material, and the vapour is also released by 

pressure via molecular diffusion (Weber, 2011).  

Numerous researches have been conducted on the behaviour of gypsum when 

exposed to high temperatures, which resulted in the development of simulation 

models. The easiest models of gypsum behaviour are based on pure heat conduction. 

In these models, the energy used during the dehydration process is introduced as a 

heat sink or by apparent heat capacity. Heat conduction models have been used for 

single boards (Belmiloudi, 2005) and assemblies of two boards with a cavity (Thomas, 

2002). The heat conduction models are dependent on the properties of the material 

when exposed to high temperatures. These properties include the enthalpy of 

dehydration, density and thermal conductivity, which must be determined 

experimentally based on the reaction temperature. This reaction temperature is 

dependent on the partial vapour pressure and the heating rate. In most models, the 

reaction temperatures are chosen at fixed temperatures calibrated with fire tests and 

have been found to give reasonable results from standard engineering applications 

(Weber, 2011). This study used no fixed temperatures since the burning coal and coal 

shales were unknown.  

2.7.1 Thermochemistry of gypsum 

The most important mechanism of gypsum in the context of blast holes affected by 

spontaneous combustion is dehydration at elevated temperatures (Ghazi, 2007). The 

chemical reaction process occurs in two stages. The first stage transforms calcium 

sulphate dihydrate into hemihydrate. The enthalpy is in Equation 2.4: 

h(T) =  hstd + ∫ Cp(θ)dθ
T

Tstd

(2.4) 

where h (T) is the enthalpy, hstd is the standard enthalpy, Tstd is the room temperature, 

T is temperature, and cp is the specific isobaric heat capacity. Since the heat of reaction 

is the difference of the enthalpies, it is related to the difference in heat capacity by 

Equation 2.5:  



27 

∆h(T) =  ∆hstd +  ∫ ∆Cp(θ)dθ 
T

Tstd
(2.5)      

        

Where ∆h is the specific enthalpy of phase change, ∆hstd is the specific enthalpy of 

phase change at room temperature (Ghazi, 2007). 

In both stages, part of the solid mass is transformed into water vapour. The 

corresponding loss of mass in each reaction can be calculated using stoichiometric 

calculations. The molecular mass of dihydrate is 17g/mol, and the molar mass of water 

is 18g/mol (Ghazi, 2007). The loss after the two reactions is 21% of the original mass, 

three quarters in the first reaction and one quarter in the second reaction. Commercial 

gypsum used for boards is not pure dihydrate, but it has certain amounts of non-

reacting anhydrite and other components. The mass of hydration can be determined 

experimentally by using TGA (Ghazi, 2007). 

2.7.2 Heat of dehydration 

A graphical representation of the enthalpies for the α-varieties is plotted in Figure 2.3. 

The curves show the enthalpies calculated from the standard enthalpies at 25 °C by 

Eq. 2.4. The enthalpies of reaction are then the differences between the curves. The 

figure shows that the enthalpy of dehydration is almost independent of temperature. 

The heat of hydration increases with temperature, while the heat of evaporation 

decreases, resulting in an almost constant total heat of dehydration. The enthalpies of 

dehydration corresponding to the reaction temperatures used in the simulations are 

indicated by vertical lines in the figure. Figure 2.3 shows the enthalpies of gypsum 

when exposed to heat. The various stages are indicated with dotted lines, while the 

original gypsum is indicated with a solid line representing gypsum before exposure to 

heat. 



28 

 

 

 

 

 

 

 

 

 

 

 

 

Taking a purity of 81% for gypsum, as determined from TGA, the heat of dehydration 

reaction relative to pure gypsum would be 650kJ/kg (Wakili, 2007). The heat of 

dehydration of gypsum is on standard tables between 642 and 663 kJ/kg (Wakili, 

2007). The principal work source of thermodynamic data on gypsum in the literature is 

work done by Kelly, et al. (1941). The work provides a complete set of thermodynamic 

properties for several reactions. The dehydration due to fire produces a mixture of the 

two forms. Furthermore, the enthalpy of the different reactions depends on the 

temperature. Values in the literature are given in room temperature and atmospheric 

pressure conditions and must be adjusted to higher temperatures when used in models 

since the reactions will occur at a higher temperature. 

Kontogeorgos & Founti, (2012) provided a framework that can facilitate the detailed 

simulation of gypsum board thermo-chemistry at ambient and elevated temperature 

conditions. The paper reviews gypsum board thermo-chemistry, presents a 

methodological approach for the calculation of composition and reaction energy, and 

focuses on methods calculating the ‘kinetic triplet’. The chemical kinetics of three main 

reactions that take place when a gypsum board is exposed at elevated temperatures: 

evaporation of free moisture content, dehydration of chemically bound water and 

Figure 2.5: Enthalpies for gypsum products (Wakili, 2007) 



29 

crystal mesh reorganization were investigated using Differential Scanning Calorimetry 

measurements under non isothermal conditions and in an inert atmosphere. 

Experiments using samples of deionized water and commercial gypsum board were 

carried out at temperatures up to 600 °C, with different heating rates. Mass and energy 

balance equations were considered in order to define the initial composition of a 

gypsum board and the energy that is absorbed/produced after the completion of the 

examined reactions. Model-free and model-fitting approaches were used for the 

definition of the kinetic parameters of the examined reactions. The approach minimizes 

the need for expensive and detailed experiments necessary for the determination of 

the gypsum board behaviour at elevated temperatures (Kontogeorgos & Founti, 2012). 

2.8 Summary 

The chapter defined spontaneous combustion and described in detail the factors that 

cause its occurrence. The influence of pyrite on the spontaneous combustion of coal 

was also discussed in light of the past and present literature. The methods of predicting 

spontaneous combustion liability of coal were mentioned and discussed, their 

applications and limitations indicated. The chemical inhibitors used to prevent CSC 

were discussed and their benefits stated. .  Thermal decomposition, thermochemistry 

and heat of dehydration of gypsum were also discussed in detail. 

  



30 

3 RESEARCH METHODS 

3.1 Introduction 

This chapter discusses the various instruments which were used to collect and analyse 

data. It further describes in detail the geometry and nature of the holes and stockpiles 

used to collect data and how data was collected using various instruments. 

3.2 Sources of data 

3.2.1 Data from the hot-holes 

Hot-hole data was acquired from three drilled holes. The holes were drilled on the 

interburden material overlying the No.2 seam coal. The drilled interburden consisted 

of shale, which was undergoing spontaneous combustion.  The three holes were drilled 

15m apart, and each hole was drilled 16m deep. Figure 3.1 illustrates the spraying 

machine and the hole sprayed with gypsum.  

 

 

 

 

 

 

 

Data from the holes was acquired by using TEMPCO 305K hand-held digital 

thermometer. This is a hand-held portable digital thermometer designed to use type K-

thermocouples with connection via industry-standard mini-plugs. This instrument’s 

Figure 3.1 : Hot-hole with spraying machine 



31 

measuring range is from -500C to 13000C. It has a resolution of 0.10C to 199.90C and 

10C to 13000C with a reading rate of 2.5 times per second. The accuracy of this 

instrument is 0.3% + 1oC from -500C to 10000C and accuracy of 0.5% + 10C from 

10000C to 13000C (RS Thermocouple Selection Guide, 2020). Data from the holes was 

also acquired using the 64 channel NI CDAC (4 x NI9213) temperature card 

instrument. This instrument has 64 channel CMS software, and the probes are 32 x 

20m type K-thermocouples with 30m extensions. 

Both TEMCO 305K and 64-channel instruments were fitted with RS PRO type K-

thermocouples.  The thermocouple is a sensor used to measure temperature in 

different processes. It consists of two wire legs made from different metals joined 

together at their two ends to form two junctions (RS Mineral Insulated Thermocouples, 

2020). The hot or measuring junction is connected to the body whose temperature is 

going to be measured. The cold junction or reference junction is connected to a body 

of known temperature. When the measuring junction is placed on something hot, a 

voltage or potential difference between this and the reference junction occurs. Using 

thermocouple reference tables, this voltage can then be converted into a temperature 

measurement (RS Thermocouple Selection Guide, 2020). This process is also known 

as the see beck effect. The thermocouples temperature probes have durable 

construction and feature a 310 stainless steel mineral insulated flexible sheath that can 

be bent and formed to suit a wide range of applications (RS Mineral Insulated 

Thermocouples, 2020). The thermocouple has a single element insulated junction for 

a reduction in electrical interference. One of the thermocouples is terminated with a 

miniature flat pin plug for a quick and easy connection, as illustrated in Figure 3.2. 

 



32 

 

 

 

 

 

 

 

 

 

3.2.2 Data from stockpiles 

An actual bituminous coal stockpile situated at the run of mine (ROM) pad was used. 

The geometry and parameters of the coal stockpile are typical of the Witbank Coalfields 

deposits. The geometry of the stockpile is of a truncated quadrangular pyramid. The 

height of the stockpile is 1.7m, and the width of 7m, corresponding to the haul truck 

used to tip the stockpiles. The length of the stockpiles was 10m each at the horizontal 

base. The slope angle of the stockpiles was 400. The fragmentation of the coal was 

mainly formed by coarse particles with a diameter of less than 15cm with an assumed 

particle size of 5cm. 

 A medium-scale test on two stockpiles of 60 tonnes each was carried out in this study. 

Stockpiles S1 was treated with gypsum, while Stockpile S2 was left untreated (control 

point) for 21 days at Khwezela Colliery in order to examine the inhibitory effects of the 

antioxidant on coal self-heating. Two 60T stockpiles from 2-Seam coal, which are 

known to be prone to spontaneous combustion, were used. At the beginning of testing, 

the temperatures of both the stockpiles were recorded, and they had similar 

temperatures. Both stockpiles were divided into six sections, namely; A1, A2, A3, A4, 

A5 and A6, as illustrated in Figure 3.3. The portions A1, A2 and A3 areas were sprayed 

with a single coat for 10 minutes using 3 kg powdered gypsum, while A4, A5, and A6 

areas were sprayed twice using 6 kg of powdered gypsum (Onifade et al., 2021). 

Figure 3.3 shows a treated coal stockpile with corresponding sides. 

Figure 3.2 Type K-Thermocouple. (RS Thermocouple Selection Guide, 2020) 



33 

 

 

 

 

 

 

 

 

 

The stockpiles were placed 15 m away from each other to minimise the influence of 

one stockpile on another due to weather conditions. Sections A1 was on the Northern 

part, A5 and A6 were on the Eastern part, A4 was on the Southern part, A2 and A3 

were on the Western part. This was to ensure that an area to area comparison was 

reliable and consistent. Gypsum is a soft sulphate mineral composed of calcium 

sulphate dihydrate, with a chemical formula CaSO4 * 2H2O (Dolezelova, et al., 2018). 

Gypsum was considered due to its wide availability and low cost. 

 

Data from stockpiles was acquired using FLIR E85 advanced thermal imaging cameras 

for electrical and mechanical applications. The cameras offer the superior resolution 

and range performance needed to identify hot spots quickly. The camera has up to 

161 472-pixel resolution and a larger, more vibrant liquid crystal display (LCD) screen. 

The camera is fitted with high-resolution infrared detectors up to 464 x 348 for crisp 

detailed images. It measures wide temperature ranges from -400C to 1200C, 00C to 

6500C and 3000C to 15000C (RS Thermocouple Selection Guide, 2020). Figure 3.4 

illustrates a thermal image of the treated stockpile captured by the FLIR E85 camera. 

 

Figure 3.3 Treated coal stockpile with corresponding sides 



34 

 

 

 

 

 

 

 

 

 

 

 

3.3 Method of data collection 

3.3.1 Data collection from hot-holes 

TEMCO 305K was connected with a 20m long type K-thermocouple wire. One end of 

the thermocouple with two metal pins was connected to the TEMCO 305K instrument. 

The temperature sensor end was allowed to reach thermal equilibrium with the 

atmospheric temperature before being inserted into the hole. The sensor end was 

lowered 16m to the bottom of the hole to record the temperature. The measurement 

was recorded only after the instrument stopped reading the temperature. At this point, 

the temperature displayed on the instrument was the temperature measured by the 

sensor at the point where the sensor was suspended.  The process was repeated at 

every 1m interval by pulling the type K-thermocouple 1m up the hole so that 

temperature readings are recorded every meter of the hole in order to cover all the 

lithological characteristic of the holes. This process was done from 06h00 to 16h00 

every 2-hour interval for 21 days from 21 August 2020 to 10 September 2020. Sixty-

four channel NI CDAC instrument was connected with 48 type K-thermocouples.  

Figure 3.4 FLIR E85 thermal image 



35 

3.3.2 Data collection from stockpiles. 

The testing equipment consisted of a compressor, powder mixer, spray gun, hose and 

spray assemble, as illustrated in Figure 3.1. While the compressor is used to spray the 

gypsum powder, the powder mixer makes the pulverised gypsum airborne to provide 

continuous spraying capabilities. The powder mixer also controls the whole process 

and has a lever to adjust the spraying speed. 

3.4 Method of data analysis 

3.4.1 Data analysis of holes and stockpiles 

A t-test was used to determine if there is a significant difference between the means 

of the stockpiles and holes as it is freely available with MS Excel and easy to use. The 

Two-Sample t-test analysis tool tests for population equality means of each sample 

(Maree, 2014). The t-test tools employ different assumptions: that the population 

variances are equal, that the population variances are not equal, and that the two 

samples represent before-treatment and after-treatment observations on the same 

subjects.   

A t-statistic value, t, is computed and shown as "t Stat" in the output tables for all three 

tools. Depending on the data, this value, t, can be negative or nonnegative. Under the 

assumption of equal underlying population means, if t < 0, "P (T <= t) one-tail" gives 

the probability that a value of the t-statistic would be observed that is more negative 

than t. If t >=0, "P(T <= t) one-tail" gives the probability that a value of the t-statistic 

would be observed that is more positive than t. t Critical one-tail gives the cut-off value 

so that the probability of observing a value of the t stat greater than or equal to t Critical 

one-tail is Alpha. P(T <= t) two-tail gives the probability that a value of the t-statistic 

would be observed larger in absolute value than t. P Critical two-tail gives the cut-off 

value so that the probability of an observed t-statistic larger in absolute value than P 

Critical two-tail is Alpha (Maree, 2014). Figure 3.1 indicates all variables which are 

measured using t-test 

 

 

 



36 

Table 3.1 t-test: Two samples assuming unequal variances 

 

 

Statistical analysis of data was used to assess the performance of gypsum on the hot-

holes and coal stockpiles. A sample assuming unequal variances was used. 

Furthermore, the mean and variance of holes were determined and compared. A 

confidence level of 95% on a two-tailed test was chosen for the study. A 0.05 (5%) 

significance level resulted in critical values of 2.1, 2.0 and 2.0 for the same side of the 

stockpile, treated stockpile and holes, respectively. After the analysis, any value less 

than the critical value would imply that gypsum did not have a significant effect. 

However, any value greater than the critical value would imply that gypsum significantly 

affected the stockpile and holes temperature.  

On the stockpiles, the temperature measurement per day was graphically represented 

and compared to atmospheric temperature. This was done to determine if atmospheric 

temperature influences the stockpile temperature and to extract any meaningful 

relationship between stockpile temperature and atmospheric temperature. This was 

done for every area measured on the stockpile for the duration of the experiment (A1 

to A6 as per Figure 3.2). Each area of the treated stockpile was compared to a similar 

area on the stockpile that is not treated with gypsum in order to determine the effect of 

gypsum on the stockpile. The average temperature of each side of the stockpile was 

calculated, and corresponding sides were compared to determine the effectiveness of 

gypsum. On the treated stockpile, the average temperature of each side was 

t-test: Two-samples assuming unequal variances 

 Stockpiles 

 S1W6 S2W6 

Mean 50.2 95.0 

Variance 167.1 3322.1 

Observations 22.0 22.0 

Degree of freedom(df) 23.0 

T stat -3.6 

P(T<=t) two-tail 0.0 

T Critical two-tail 2.1 



37 

calculated and then compared to each other to determine the extent to which a higher 

concentration of gypsum affected the temperature of the stockpile. The overall 

temperature of the untreated and the treated stockpiles were calculated and compared 

to determine the extent to which gypsum inhibits the temperature of the stockpiles.  

The temperature was measured on the three blast holes before treatment with gypsum 

to establish the initial temperature. The interburden above the No.2 seam coal consists 

mainly of sandstone and shale with a dark white colour. On an air-dried basis, the no.2 

seam coal contains 31.59% ash, 26.73% volatile matter and 22.56 calorific value. The 

holes H1 and H2 were treated with gypsum while H3 was not treated. The temperature 

of each hole was measured at every 1m interval, where 0m is the collar of the hole. 

The average temperature of each hole per day was calculated and compared to the 

atmospheric temperature. This was to determine the influence of atmospheric 

conditions on the in-hole temperature. The average in-hole temperature of each hole 

was compared against one another in order to determine the extent to which different 

concentrations of gypsum affected the in-hole temperature of the two sprayed holes 

against the controlled hole. 

3.5 Summary 

This chapter discussed the sources of data. The use of a TEMCO 305K digital 

thermometer and 64-Channel thermocouple for in-hole temperature measurement, the 

FLIR E85 thermal camera used to collect stockpile data, and the characteristics and 

geometry of the stockpiles and hot-holes were discussed in detail. The holes were 

spaced 15m apart to minimize the thermal influence of each other. The composition of 

gypsum and its characteristics were also discussed, including how gypsum was 

sprayed to the two hot-holes and two coal stockpiles. The chapter concluded with a 

statistical analysis, which was used to assess the performance of gypsum on hot-holes 

and stockpiles. 

  



38 

4 RESULTS AND DISCUSSION OF COAL STOCKPILES 

4.1 Introduction 

The comparison between the atmospheric temperature and stockpiles is done for all 

22 days of the study. Each side of the stockpile is compared to the atmospheric 

temperature. Further analysis is done by comparing similar sides of the stockpile to 

each other for 22 days. MS Excel was used to represent the findings graphically, and 

t-test analysis was done on a test statistic to assess the significance of gypsum on coal 

stockpile temperature. Lastly, the comparison of the two sides of the treated stockpile 

was done to determine the significance of a higher gypsum concentration on the 

spontaneous combustion of coal stockpiles. The graphical representation of 

measurements taken for 22 days is done together with statistical analysis using a t-

test. 

4.2 Stockpile temperature and atmospheric temperature 

To easily interpret the results and observations from the two stockpiles, the following 

naming convention was adopted: 

The measurement points A1, A2, and A3 are west side of the stockpile. When the 

measurements are on the treated stockpile, they are labelled S1W. S1 represents