Detecting coalfires with remote sensing: a comparative study of selected countries
Coal fires, both underground and on the surface, are a serious problem in most major coal-producing countries of the world. Combustion can occur from both natural and anthropogenic causes either spontaneously on exposure of coal to air, or as a result of ignition from lightning strikes or forest fires. The anthropogenic fires are due to poor mining techniques and human activities near the coal seams. Once started, they are difficult to extinguish leading to operational difficulties and causing local pollution and endangering human security. However, coal fires emit large quantities of carbon dioxide (CO2) along with several other noxious gases such as carbon monoxide, oxides of sulfur and methane that are significant enough to create impact on global scale. The scientific study of coal fires thus becomes essential to track them in remote locations. This paper discuses the significance of satellite remote sensing as a reliable tool to detect and monitor coal fires in selected countries, with a review of coal fires and related environmental issues. It notes the use of multi-spectral space-borne thermal remote sensing data in returning reliable results in detecting and measuring coal fires.
Coal fire: the problem
The widespread extent and intensity of subsurface and surface coal fires poses serious problems from many perspectives. The fires may occur spontaneously (spontaneous combustion) as, in the right circumstances coal will catch fire of its own accord in the presence of air. Coal fires may be ignited through lightning strikes, bushfires or through human agency. Combustion can occur either within the coal seams themselves, in piles of stored coal or in spoil-dumps on the surface. Such fires are widespread in many locations of coal-producing countries, but are of particular preponderance in China, India, Indonesia, in parts of USA, and in Australia (Fig. 1). Some of these fires are been continually burning for decades without being effectively controlled. Some of these fires have endangered human safety, altered local vegetation patterns and have been associated with wider fires such as peat bog and forest fires, thus potentially contributing to the alteration of global climate. Later on in this paper, we give a brief account of coal fire occurrence and history from selected coal producing countries.
A considerable range of environmental and economic issues are directly and indirectly related to coal fires. These problems affect a range of geographical scales from the local to global, from short-term to the long-term, from reversible to irreversible damages.
The local impacts, some of them being irreversible, may concern:
- environmental damage and degradation of land, heat effects on surrounding rocks and land subsidence, desiccation of forests, lowering of water quality, and the smoke-related air pollution which can effect human health and safety.
- wasteful consumption of a potentially valuable resource,
- operational difficulties related to mining by increasing the cost of production or by making existing operations uneconomical.
The global scale is invoked because of the substantial emissions from coal fires of CO2 and methane (CH4), which are the major contributors to the enhanced greenhouse effect and climate change. As coal will continue to provide the major source of power in some of these countries and hence will continue to be mined, the study of coal fires assumes great significance.
In terms of air pollution, coal fires emit a range of substances such as the traditional air pollutants, sulfur oxide (SOx), nitrogen oxide (NOx), and carbon monoxide (CO), and particulate matter along with compounds that fall into the ‘air toxics’ category. As well as being visible, coal fire emissions have a strong odour. Coal fires, be they in a power station or as a result of spontaneous combustion, emit their carbon (C) mostly as CO2 which is a strong greenhouse gas. In addition, spontaneous combustion also emits CH4 (not from coal seam gas but formed in the combustion/oxidation process) which on a mass basis is 21 time more powerful as a greenhouse gas than CO2. The CO2/CH4 ratios from spontaneous combustion are highly variable but can increase the climate forcing potential of these emissions by up to 30%.
Our study, presented in this paper, is placed in this context. It first discusses the chemical properties of spontaneous combustion and the case histories of fires in the major coal-producing countries of the world, and illustrates how to detect these fires with the help of remote sensing. In addition to providing an assessment of the possible impacts of these fires, it looks at how best to determine their occurrence, extent and spread and outline the levels of resultant impacts. In the next section, we give the background as to why or how these fires occur and a brief history of their occurrence in the main locations.
Coal: properties and the burning process
Coal is a readily combustible rock containing more than 50% by weight of carbonaceous material. There are substantial reserves of coal in the world, and coal accounted for 30% of the worlds primary energy production from fossil fuels in 2003. Coal is formed from plant materials as the result of compaction by burial and subsequent induration (the temperature rises with depth of burial). These remains were initially deposited in a swampy basin in the form of vegetation which would then have become peat. Unpredictable amounts of other substances such as sulfur, chlorine, sodium, and other elements can also be deposited in the swampy basin and are then found in the coal. The physical properties of coal, such as colour, specific gravity, and hardness, vary considerably. This variability depends on the composition and the nature of preservation of the original plant material that formed the coal, the amount of impurities in the coal, derived from soil and silt being co-deposited with the parent material and the amount of time, heat and pressure that has affected the coal since it was first formed. Time, heat and pressure also determine the degree of maturation of the sequence, which according to the increasing amount of carbon, is classified as lignite, sub-bituminous coal, bituminous coal, and anthracite. Rank is another index of coal quality. This is a measure of brightness (reflectivity) of the coal as measured microscopically and is function of the vitrinite content – one of the microlithotypes in coal.
Combustion of coal is a chemical process which can be defined in a simplified form as:
COAL + O2 ? CO2 + Energy (1)
Other substances present in the coal will also combust; for example iron pyrites (FeS) will oxidize to form sulfur dioxide (SO2). Coal can be represented by a large organic molecule of somewhat indeterminate and variable composition. For dry coal, equation 1 can be depicted as:
C100H74O11 + 113O2 ? 100 CO2 + 37 H2O + 4.2×108 J/kmol O2 (2)
In the first part of the equation 2, chemical absorption of oxygen occurs on the coal surface, (equation 3), and is an exothermic reaction.
C100H74O11 + 17.5 O2 ? C100H74O46 + 2.5×108 J/kmol O2 (3)
However, the heat of absorption is difficult to isolate as CO2 is invariably formed in the process. Therefore the value for the heat of absorption should be viewed with caution. The rate of equation 2 increases with rising temperature which is fundamental to spontaneous combustion.
Spontaneous combustion and coal fire
The potential for spontaneous combustion of coal lies in its ability to react with oxygen at ambient temperature. When coal is exposed to oxygen, heat is evolved (equations 2 and 3). The temperature of the coal may then start to rise to an extent dependent on how easily the heat generated by the oxidation can be carried away, i.e. the degree of insulation. Once the temperature of the coal rises it may well continue to do so if sufficient oxygen (air) is available, as the oxidation rate coefficient also increases with temperature, but this is offset to the extent that heat losses also increase as the oxidizing coal heats up. If it reaches somewhere between 230°C and 280°C, then the reaction becomes so rapid that the coal reaches ‘ignition’ or ‘flash’ point and starts to burn.
It has been well known to coal miners that the most fire-prone coal is often low in rank, probably because low-ranking coal has a higher porosity which more readily allows the ingress of oxygen. However, this is less obvious in laboratory experiments probably because of small sample sizes compared to the scale of heterogeneity, both vertically and horizontally, within the coal seam. The pores in low-ranking coal are often filled with moisture which blocks the oxygen from getting in, but when the coal is exposed the moisture drains away allowing oxygen to get in. A few fires are caused by an external heat source speeding up the oxidation process and setting fire to the coal. A bizarre example would be the ‘spontaneous’ combustion triggered by the illegal distillation of alcohol in Indian coal mines. Unregulated digging of coal in surface or underground deposits can also lead to the beginning of a fire. In Indonesia, forest fires are known to have triggered coal fires.
Fires can be located on (or very near) the surface or underground and can burn with an open flame or take place as smouldering combustion. An open fire is defined as a coal fire that burns in direct contact with the atmosphere usually with visible flames. Open fires occur in exposed seams in open pit mines (also called open cast) and in stock piles particularly of reactive coals. These can be controlled by water spraying.
For subsurface combustion, the requisite oxygen enters via fissures connected to the surface, through old abandoned mine tunnels which have not been properly isolated, or via fissures resulting from subsided land over such mines. In many subsidence prone old coal mining areas such as the Raniganj in eastern India, breathing of oxygen through cracks hse caused subsurface fires. For spoil dumps (i.e. the dumped overburden), the ground is unconsolidated so that air can get through, especially with a sloping surface exposed to the wind. Subsurface coal fires and subsidence thus have a close relation, one being at once the cause and consequence of the other. The following figure (Fig. 2) describes the relations more clearly.
Coal fires and surface temperatures
It is obvious that coal fires will heat the ground around them even when they are located underground, provided they are not at a great depth. This fact of ground heating provides a convenient means of detecting the coal fires using satellite or airborne remote thermal sensors. Indeed it is the only tool to survey wide areas in remote locations of Asia, particularly China, India and Indonesia, where coal fires are prevalent. The methodology in the use of remote sensing is outlined below.
Remote sensing, surface temperature and coal fires
The process of remote sensing can be briefly described by the following steps:
- Energy source - illuminates or provides electromagnetic energy to the target of interest.
- Radiation - energy travels from its source to the target.
- Interaction with the target - depending on the properties of both the target and the radiation.
The previous three steps apply to remote sensing making use of reflected radiation rather than detection of emitted radiation of the target. The following steps apply to both reflected and emitted radiation:
- Interaction with the atmosphere – reflected and/or radiated energy from source target is transmitted through and interacts with the atmosphere. The degree of interaction depends both on atmospheric composition along the ray path and on the height of the sensor (e.g. satellite or airborne).
- Recording of energy at the sensor - a sensor collects and records the electromagnetic radiation that has been transmitted through the atmosphere.
- Reception and processing - the data recorded by the sensor is received at a ground station where the data are processed into an image and distributed.
- Interpretation and analysis - the processed image is interpreted, visually and/or digitally, to extract information about the illuminated or emitting target.
- Application - the final element of the remote sensing process is achieved when it reveals new information or assists in solving a particular problem.
In the electromagnetic spectrum the 3-60?m region is referred to as the thermal infrared region. Practically, in the region with wavelengths longer than 15?m the energy radiation from earth’s surface is insignificant and it is complicated to acquire a signal. Within the overall thermal infrared region, the 3-5?m and 8-14?m regions are used in thermal remote sensing as in the intervening part of the electromagnetic spectrum the energy is greatly absorbed by the atmospheric gases.
Thermal-infrared sensing exploits the fact that everything above absolute zero (-273°C) emits radiation in the thermal infrared range of the electromagnetic spectrum. Thermal infrared radiation of an object is controlled mainly by several factors: the emissivity of the object, its geometry and its temperature. A perfect blackbody (an object whose temperature of emissions is controlled only by temperature) has a predictable range of wavelengths that varies as the temperature in Kelvins, and that moves to shorter wavelengths as the temperature increases (Wiens’ Displacement Law). Emissivity and geometry alter this wavelength range, primarily by absorbing at wavelengths characteristic of the chemical composition of the object. The energy emitted is described by the Stefan-Boltzman Law, which relates the energy to the fourth power of the temperature. For objects with an emissivity of 1, the observed “brightness temperature” is equivalent to the kinetic temperature of the object. The conversion from brightness (remotely observed) temperature to kinetic temperature can be easily made when the characteristic emissivity of an object is known. These calculations do not take into account the interactions with the atmosphere, which must be separately considered. However when thermal contrast between objects is the intended observation, as in fire detection, atmospheric interference removal and conversion to precise kinetic temperatures is less important to the object of the exercise.
Thermal infrared sensors record the spatially averaged received infrared radiation from various objects within the target footprint. The energy recorded by a space-borne sensor is the combination of energy radiated by an object and the energy absorbed and reemitted by the atmosphere (Fig. 3).Since the differences in temperature and emissivity from one object to another are often considerable, an infrared image can exhibit a large amount of contrast. The sensors carried by aircraft or spacecraft, sensitive to this (infrared) region, provide a possible means of making synoptic measurements of land surface temperatures.
Many commercial and research satellites are now acquiring data in the thermal infrared region (8-14?m) all over the world. Among them Landsat7 ETM+ band 6 thermal data has 60m spatial resolution which is the highest in commercially available thermal satellites. Landsat 7 produces two thermal images, one acquired using a low gain setting (referred as band 6L) and the other using a high gain setting (referred as band 6H). Since May 2003, Landsat 7 ETM+ is semi-operational due to failure of a mechanism to properly align rows of pixels. Landsat 5 TM data, acquired in a single band at 120m spatial resolution, can in some instances be used to provide needed data within the Landsat 7 images. Extensive work is being done to provide the best quality data possible under the circumstances. In addition, archived Landsat 5 TM data from 1984 to the at least 2007 is available. Another useful thermal scanner is aboard the multi-sensor TERRA satellite, namely ASTER. It has five channels in the thermal infrared region (8.125-8.475?m, 8.475-8.825?m, 8.925-9.275?m, 10.25-10.95?m, 10.95-11.65?m) at 30m spatial resolution. Different methods have been developed by researchers to extract emissivity from ASTER data that can provide better surface temperature estimation in the area under consideration. Some ASTER data has also been used to compensate for Landsat 7 ETM+ errors. At a coarser resolution, AVHRR scanners with a spatial resolution of 1.1.km have been aboard successive NOAA satellites since the 1980s, providing continuous data. Since 1999, thermal data from 19 different channels at 1 km resolution is available from the MODIS sensor, aboard the TERRA and AQUA satellites. All of the above satellite-based sensors are US-based. In addition, the European Space Agency has a number of thermal satellites although low-cost public access to the data is less readily available. Finally, many airborne thermal scanners exist adapted to detailed work; the Australian Daedalus scanner will be mentioned below. Since sensors and satellite systems are undergoing rapid development, the images available may change from time to time and knowledge of them needs to be updated whenever undertaking a particular project.
Coal fires on the surface, when present as flaming combustion, emit significant thermal energy that is easy to detect by any remote sensing scanner. Some of these may be at a high enough temperature to become visible in wavelength bands shorter than the thermal infrared, indeed even in the visible wavelengths. However, in the case of a subsurface coal fire the surface heating is comparatively subdued and may be masked by the solar heating or reflected solar thermal radiation during the day. In that case it is necessary to use night-time remote sensing data to reveal and measure the extent of heating.
Coal fire detection using remote sensing has three major steps:
- Acquire a thermal image (preferably night) of the area under investigation using remote sensing and process digitally to create a surface temperature map to reveal the temperature anomalies,
- Acquire information about local geological setting, temperatures of coal fire vents and different land covers through field survey,
- Use geological and other field data to eliminate anomalies other than coal fires and produce a final temperature map calibrated with field collected temperatures to reveal the coal fires.
As discussed above, the process is not exactly simple, and one needs to keep several parameters in mind, particularly the atmosphere between the coal fire and the remote sensor which plays a significant role in the accuracy of the surface temperature estimation. One must also know the nature of the affected surface in terms of albedo (reflectivity), emissivity and thermal conductance. Soil moisture also affects surface temperature. A typical diurnal temperature profile is shown in Fig. 4. To avoid surface heating due to daytime solar radiation, night-time images are needed but they are not always readily available. Table 1 shows how the thermal properties of different surface materials may vary.
Table 1: Thermal properties of some materials (CGS units for 20°C)
Source: Kahle A.B., 1979
Other methods for coal fire detection
Other methods for detection of coal fires are local and ground-based in nature as compared to satellite or airborne remote sensing techniques. Ground-based survey methods require access to the collieries which may be difficult to obtain for several reasons: the nature of the terrain, difficulty of obtaining permission in visiting controlled zones, presence of forests and lack of roads are the important obstacles have been often faced by the field survey experts. Use of these methods also commonly involves some a priori knowledge that a coal fire exists or has been present, thus precluding the possibility of prediction.
The extent and intensity of subsurface combustion can be ascertained through borehole temperature measurements. Indeed, this was the main tool to detect subsurface coal fires until the 1960s. The advantage of this method is that temperature measurements are taken close to the fire. However this method requires time and effort to drill, and was generally only used in specific instances such as fire management, identification of deep subsurface fires or maybe to validate processed remote sensing data. It remained difficult to gather enough data to produce a large-scale synoptic view.
Sedimentary rocks contain natural radionuclides such as isotopes of potassium (K-40), rubidium (Ru-87) uranium (U-235, U-238) and thorium (Th-232). Uranium and thorium nuclides decay via emission of ? and ? particles; during this process they are transformed into radon gas, containing radon (Rn-219. Rn-220, Rn-222) with half-lives ranging from 3.9 sec to 3.82 days (the Rn nuclides decay further to isotopes of lead). Radon gas diffuses through fissures to the surface where it can be detected and may accumulate, for example in the basements of buildings. The emanation rate is a function of several variables including U and Th concentrations in the sedimentary rocks, the effective porosity of the rocks and the extent of fissuring. It is likely that the gas is carried to the surface along with other gases such as CO2 and CH4 released in the combustion process, and CH4 from the adjoining coal seams, but the details are not well understood. In principle, if CO2 and CH4 are co-emitted one could use them as a tracer. However, the background atmospheric concentrations (370 and 1.7 ppmv respectively) preclude sensitive and accurate measurement. An array of turned cups, coated internally with an absorptive material, is distributed across the surface of a study area and the accumulation of Rn over a period of time (e.g. 30 minutes) is measured with an ionisation chamber. Xue and Winkelmann give a successful example of the use of this technique for the surface detection of heating in underground goafs (200-340m deep), where underground gas analysis suggested self heating was occurring.
Coal fires can affect the bulk resistivity of the surface strata. The resistivity is generally determined by the amount of conducting fluid contained in the strata. The resistivity is measured by inserting several metal electrodes into the earth perhaps some tens of meters apart, applying a current between the outermost pair and measuring the potential difference across inner pairs of electrodes. For constant electrode spacing, a, and if the impressed current is i resulting in a potential difference of ?V, then the resistivity is given by 2?a?V/I. In normal conditions the resistance of sedimentary rock is about 600-800 W/m but in burnt rock it goes up to 1200-3000 W/m, because of higher porosity, more cracks and lower water content.
Coal fires worldwide
Coal fires have occurred since time immemorial. Remnant baked rocks in northwest China around what were coal seams originated up to 1.5 million years BP measured according to their geomagnetic properties. Goldammer and Seibert, using thermoluminescence, dated baked rocks close to a coal seam in East Kalimantan to 13,000 years BP. Lightning strikes/forest fires were the probable igniters of outcropping coal. Archaeological remains suggest that human involvement with coal fires has occurred since at least 75,000 years BP and may well have started from observations of spontaneous combustion of naturally-occurring outcrops. In countries where coal mining started early in human history, coal fires were inevitably reported; some were responsible for mine disasters and were short-lived, others burned for considerable periods of time. The advent of open-pit mining provided greater scope for the occurrence of coal fires both in-seam and within spoil piles. However, these open fires on the surface are more easily managed, although they contribute more readily to a decrease in air quality. The fires that are burning underground pose a much more difficult management task. Major coal fires of the world, largely uncontrolled, are burning in Asia, but other large coal producers also have spontaneous combustion. A brief outline of some of the coal fires around the world follows.
Coal fires in the United States
Based on the clinkered remains in the Powder River Basin (between Montana and Wyoming), Heffern and Coates estimate that tens of billions of tonnes of coal have burned away over the past two million years ignited by forest fires or lightning strikes. While this is much larger than the total amount of coal burned for energy over the past century, the overall rate of consumption was orders of magnitude less. These naturally-ignited fires still occur and in general the coal in this region is of low rank and therefore more susceptible to spontaneous combustion.
Coal mining started in Pennsylvania, USA, mainly to make coke for iron smelting. The occurrence of the first coal fire was reported in 1772 and in 1869 it turned into a major disaster and claimed many miners’ lives as cited by Stracher and Taylor by referring to Glover. Finally it extinguished itself about a year after an attempt to pour water in the mine failed. The Pennsylvania fire had so great an impact on the local environment that it badly affected local flora and fauna, and made it a major acid rain producer in the United States. But many underground coal fires continue to remain poorly documented because they are uneconomic, intangible and unpredictable. The Centralia mine fire in Pennsylvania has been burning since 1962 and is one of the worst mine fires in the United States.
In 1962, the United States Bureau of Mines reported 223 coal fires all over the United States. The United States was the first country to apply remote sensing to coal fire detection. Using the ‘Reconofax’ thermal scanner on an airborne platform, Slavecki and Kunth, and also Greene et al. studied fires on waste coal and subsurface coal in Pennsylvania, the state where coal fire is still a serious problem. Greene et al. also studied the depth of fire and they classified fires of three types according to their depth: shallow fires (up to 10m deep), intermediate fires (10 to 30 m deep) and deep fires (more than 30 m deep).
Coal fires in Australia
The first recorded observation of the famous Burning Mountain coal fire in Australia was in 1828 after its discovery by a local farmer. In 1829 and again in 1831 these fires were mapped with a detailed description by the then surveyor general, T.L. Mitchell. Later, Abbott recorded detailed information about this phenomenon concerning the movement of the main vent area. Bunny and Rattingan made detailed and careful contributions on the study of the Burning Mountain coal fire. A notable study was produced by Fleming that suggests the fires could have been burning since Pleistocene times. Later Ellyett and Fleming did an extensive study using a Daedalus thermal airborne scanner that operates in 8-14 ?m. Today that fire is more than 152 meters underground, and is still slowly burning the coal.
In addition to this non-anthropogenic (presumably) event, fires also occur spontaneously on open-pit coalmines in many locations such as Hunter Valley (New South Wales) and the lignite mines in Victoria and South Australia. These provide a continuing emission of greenhouse gases, those from black coal mining being assessed by Williams et al. A review of spontaneous combustion incidents in Australian black coal mining over the past 30 years has been provided by Ham. While sporadic in nature, some of these incidents have had high impact resulting in loss of life.
Coal fires in Indonesia
In Kalimantan, formerly the Borneo island of Indonesia, slash and burn is a widely-used and easy method to claim cultivable land from forests. Sometimes the fires get out of control, and become widespread. Lightning strikes may also ignite forest fires. Such forest fires sometimes ignite the coal seams that are close to the surface which become very difficult to extinguish because they often ignite in the peat layer. In East Kalimantan, baked rocks were found close to a coal seam which, using the technique of thermo-luminescence, dated the fire to 13,000 years BP. The existence of coal fires in southern Sumatra is also familiar to the coal fire research community. It has been assumed that these ancient coal fires were initially ignited by lightning. In Indonesia, the combination of violent forest fires, frequent lightning and a warm climate favour the spontaneous combustion in exposed layers of coal and peat. The collieries that have sprung up e.g. in East Kalimantan are open cut operations and fires tend to occur on the surface in areas where the coal is of lower rank – the coal deposits can be heat affected due to high geothermal gradients associated with volcanic activity and thus the rank of coal further away from such hotspots has a lower rank. Although Indonesia is the world’s fifth largest coal producer, many coal operations are rather small and a large amount of coal is mined by ‘petis’ or illegal miners around the official collieries in the central parts of Kalimantan. Consequently, it is difficult to pinpoint the exact cause of such fires.
Coal fires in India
Coal mining began in India in the late 18th century at Raniganj, about 250 km northwest of Calcutta in what are now the Eastern coalfields. Underground fires have been known there for the past 100 years or more and they occur in what was shallow, almost cottage industry type of mining. Studies based on Landsat 5 thermal data with inputs from topographical maps and census data show that these fires are endangering the lives of hundreds of thousands of people.
The neighbouring Jharia coal belt has also experienced fires throughout many decades and, as with Raniganj, these fires are often associated with shallow underground coal dug out with basic equipment such as pick and shovel. In the past 30 years or so the rate of coal extraction from Indian mines has accelerated such that India is now the third largest coal miner in the world. Jharia along with the Raniganj coalbelt, now produces about one third of the coal in India. In addition, there is a large illegal coal economy that runs parallel to the official one and adds to the causes of coal fires.
Many researchers, such as Bhattacharya, Cracknell and Mansoor, Reddy et al., Saraf et al., Prakash et al. have worked on the Jharia coal fires. Using airborne predawn TIR (thermal infrared) and daytime multispectral data Bhattacharya et al. could distinguish the fires from the background. To detect the coal fire another attempt was made by Mukherjee et al. using pre-dawn airborne thermal data. They also attempted to estimate the depth of the fire using a linear heat flow equation. Cracknell and Mansoor first used Landsat-5 TM and NOAA-9 AVHRR data and found that night time NOAA data was quite useful to isolate the warm areas from the background. Reddy et al. used the short-wave infrared (SWIR) region of the electromagnetic spectrum, which is covered by Landsat TM bands 4, 5 and 7. They described that the hotspots found in the image corresponded well with the field measurements. In the same area, using Landsat TM bands 6 and 7, Saraf et al. found that comparatively high temperature zones must have surface fires, whereas the less warm areas should have subsurface fires. Later Prakash et al. used the Landsat TM TIR and SWIR bands to identify surface and subsurface fires separately. Based on a dual band approach for TM data, Prakash and Gupta attempted a method for calculating the area of surface fires. The main problem they faced while developing this method was reflected solar energy in the SWIR region in the daytime images.
Coal fires in China
China is the world’s largest coal miner, extracting over 1 billion tonnes annually, for its own consumption. Coal fires are an immense environmental problem in northern China. A study by Huang et al. using Daedalus data, presented a frightening picture of the extent of coal fires. In Xinjinag and Ningxia Hui regions several ITC based researchers have worked on coal fires since 1986. By using pre-dawn airborne thermal scanner data, Yang identified several coal fires in these areas, which correlated well with field observations. Later Wan and Zhang carried out a detailed study in the same area. They used daytime Landsat TM band 6 (TIR) data to estimate the relative amount of solar illumination during the overpass time, which was used to correct for the effect of topography. Because the spatial resolution of Landsat 5 thermal band is quite poor (120m) and cannot detect small fires, Zhang et al. tried a sub-pixel temperature estimation method and found if a pixel has a considerablly higher temperature than that of the surrounding background, is easy to detect even if smaller than the pixel footprint. They also highlighted how a fire can be identified if the background temperature is known. Cassels attempted modeling of underground coal fire in the Kelazha area of northern China with the inputs from a 3D geological model that has returned significant results. By analyzing SWIR spectra of rocks, Zhang Jianzhong identified the burnt rocks, which is also an indication of coal fire. In 1997, Peng et al. attempted fire depth estimation in the Kelazha area. In Xinxiang province, Wang identified coal fire-affected areas with ASTER and Landsat TM data.
In the Wuda mining region, situated in Inner Mongolia, an extensive study has been done on coal fires using satellite-derived emissivity that returns a more reliable surface temperature. Because emissivity values vary somewhat with the change of landcover, satellite-derived emissivity values can increase the accuracy of kinetic surface temperature calculation which was one of the outcomes of this research.
Greenhouse gas emissions from coal fires
Over the past two centuries, anthropogenic emissions of greenhouse gases (GHGs) have increased to an alarming situation. This stead increment of GHGs in atmosphere act as a blanket that retains solar radiation in the atmosphere leading to global warming. Among the all GHGs, CO2 has a significant status in this phenomenon. Since pre-industrial era the concentration of CO2 has increased from 280ppm to 370ppm (2005 Mauna Loa annual average data). This rise in the concentration of CO2 is not only influenced by human activity such as rapid industrialization and deforestation, but also by some geo-natural events such as coal fires. The greenhouse gases, emitted from all sources, have increased the global mean surface air temperature between approximately 0.3 and 0.6ºC since the late 19th century and have caused serious consequences for low-lying coastal areas as a result of rising sea levels from both thermal expansion and melting of ground-based glacial ice..
Presently the impacts of coal fires on climate change and their contributions to global warming are increasingly getting expert attention. Recent coal fire studies in China, one of the major producers of coal, estimate that the country contributes 0.3% of the total world annual output of CO2 caused by fossil fuels. Other researchers put this amount at a much higher level, 3% of the world's total, neither of which is a negligible amount. However, the above mentioned estimations are based on indirect methods such as the total coal burnt in a certain area. Presently some hyperspectral remote sensing-based methods are being developed that use the absorption features of CO2 in a particular part of the electromagnetic spectrum to quantify CO2 emissions. Finally, coal emissions come from a combination of naturally and anthropogenically ignited coal fires. Any assessment of these from a GHG perspective should attempt to apportion these emissions into these two categories. If, however, it is viewed that any emission from fossil fuels is undesirable, this separation becomes unimportant.
Coal fire is a widespread problem with long and complex histories in most coal-producing countries. Their extent and frequency varies according to the local climate, terrain and social factors such as the prevalence of illegal mining or mining techniques. The impacts of coal fires are large and wide-ranging, extending from local (pollution) to global climate change. An important problem in coal fire studies is to determine the location, extent and intensity of the fires, and in this respect, we suggest the use of remote sensing technology. Remote sensing can play a significant role in detecting and monitoring coal fires, potentially leading to the optimization of strategies for their control and thus minimizing economic and environmental impacts. Though most researchers concentrate their study primarily on coal fire detection and monitoring, the measurement of greenhouse gases emitted from coal fires needs to be considered more seriously. The coal fire-related greenhouse gases have a significant adverse contribution to global climate. It is clear that to reduce the steadily increasing greenhouse gases in the atmosphere, emissions related to coal fires need to be examined more intensively. However, as noted in the case histories, often coal fires are caused by multiple factors that are rooted in local socio-economic frameworks. Thus, to prevent them requires a concerted effort among social and physical scientists, as well as by governments.
Books and Journals
- Abbott, W. E. (1918). Mount Wingen and the Wingen Coal Measures, Angus and Robertson, Sydney, N.S.W. Australia.
- Anon (1972). The Burning Mountain, Wingen, Scone Shire Council Archive.
- Banerjee, S.C. (1985). Spontaneous combustion of coal and mine fires, A.A. Balekema, Rotterdam, pp. 18.
- Bhattacharya, A., Reddy, C.S. and Mukherjee, T. (1991). Multi-tier remote sensing data analysis for coalfire mapping in Jharia coalfield of Bihar, India, Proceedings of the Twelfth Asian Conference on Remote Sensing, Singapore, 30th October-5th November 1991 (Singapore : National University of Singapore), pp. 22-1-22-6.
- BP, 2003. Statistical review of world energy. available at www.bp.com (accessed September 15th, 2005)
- Bunny, M. R. (1967). The Burning Mountain, Wingen, N.S.W. Geol. Survey Report, GS1967/063.
- Carras, J.N., Day, S. & Williams, D.J. (1999). Measurement of greenhouse gas emissions from spontaneous combustion at the Drayton coal mine. CSIRO Energy Technology, report ET/IR 103R August, pp. 20
- Cassells, J.S.C. (1998). Thermal modelling of underground coal fires in northern China, PhD Thesis, ITC, Enschede, The Netherlands.
- Cracknell, A.P. and Mansor, S.B. (1992). Detection off sub-surface coal fires using Landsat Thematic Mapper data, International Archives of Photogrammetry and Remote Sensing, Vol. 29(B7), pp. 750-753.
- Ellyett, C.D. and Fleming, A.W. (1974). Thermal infrared imagery of the Burning Mountain coal fire, Remote Sensing of Environment, Vol. 3, pp. 79-86.
- Fleming, A. W. (1972). Investigations into Permian Geology and The Burning Mountain Coal Fire, B.Sc. (Honors) Thesis, University of Newcastle.
- Gangopadhyay, P.K. (2000). Surface Temperature Mapping and Detection of Surface & Subsurface Coal-mine Fires of the Raniganj Coalbelt (West Bengal) Using Remote Sensing and GIS, Dissertation Paper, IIRS, Dehradun, India.
- Gangopadhyay, P.K. (2003). Coalfire detection and monitoring in Northern China: A multi-spectral and multi-sensor TIR approach. M.Sc. Thesis, ITC, Enschede, the Netherlands.
- Gangopadhyay, P.K., Lahiri-Dutt, K., Saha, K. (2005). Application of remote sensing to identify coalfires in the Raniganj Coalbelt, India. International Journal of Applied Earth Observation and Geoinformation (under review)
- Gangopadhyay, P.K., Maathuis, B., van Dijk, P. (2005). ASTER derived emissivity and coalfire related surface temperature anomaly: A case study in Wuda, North China. International Journal of Remote Sensing (accepted).
- Gangopadhyay, P.K., van der Meer, F.D. and van Dijk, P.M. (2005). Atmospheric modelling using high resolution radiative transfer codes and identification of CO2 absorption bands to estimate coalfire related emissions. In: 4th workshop on imaging spectroscopy: new quality in environmental studies, 27-29 April 2005 Warsaw, Poland: Book of abstracts, ed. by B. Zagajewski, M. Sobczak and W. Próchnicki. EARSeL, 2005. pp. 92.
- Geissinger, J. (1990). Mapping Underground mine fires: The case of Centralia, Pennsylvania. The Pennsylvania, Vol. 28(2), pp. 22-26. Geographer
- Glover, L. (1998). Underground Mine Fires Sparks Residents’ Fear. Tribune Review, Greensburg, PA (May 3), A-1, A-10.
- Goldammer J.G. and B. Seibert (1989). Natural rain forest fires in Eastern Borneo during the Pleistocene and Holocene. Naturwissenschaften 76: 518-520. Greene G.W., Moxham, R.M. and Harvey, A.H. (1969) Aerial infrared surveys and borehole temperature measurements of coal mine fires in Pennsylvania, Proceedings of the Sixth International ERIM Symposium on Remote Sensing of Environment, University of Michigan, Oct. 13-16, pp. 517-525.
- Greene G.W., Moxham, R.M. and Harvey, A.H. (1969). Aerial Infrared Surveys And Borehole Temperature Measurements Of Coal Mine Fires In Pennsylvania, Proceedings Of The Sixth International ERIM Symposium On Remote Sensing Of Environment, 13-16 October, 1969 (University of Michigan), pp. 517-525.
- Ham B. (2005). A review of spontaneous combustion incidents. Proceedings Coal 2005, Australian Institute of Mining and Metallurgy, Brisbane, 26-28 April, pp.237-240.
- Heffern E.L. and Coates D.A. (2004). Geologic history of natural coal-bed fires, Powder River Basin, USA. International Journal of Coal Geology, Vol. 59, pp. 25-47.
- Huang, Y., Huang, H. and Chen, W. (1991). Remote sensing approaches for underground coal fire detection, Proceedings of the Beijing International Conference on Reducing Geological Hazards, 20th-25th October, 1991, Beijing, China, pp. 634-641.
- Kahle, A.B. (1979). Surface Thermal Properties in Remote Sensing in Geology eds. Siegal, B.S. and Gillespie, A.R., John Wiley and Sons, New York.
- Knuth, W.M. (1968). Using an airborne infrared imaging system to locate subsurface coal fires, in Culm banks, Proceedings of the Pennsylvania Academy of Science, 42.
- Lahiri-Dutt, K. and Williams, D. (2005). The coal cycle: A small part of the domestic coal supply in eastern India, Journal of Resources, Environment and Development, The Energy Research Institute, New Delhi, September.
- Lahiri-Dutt, K., Saha, K., Gangopadhyay, P.K. (2005). Human security in areas of subsurface coalfires: Locating vulnerable villages in the Raniganj Coalbelt, India. Australian Geographical Studies (submitted: under revision).
- Lahiri-Dutt, K. (2002). Location, extent and means of control of surface and subsurface mine fires in the Raniganj coalbelt of West Bengal with the help of satellite data, Final Report Submitted to University Grants Commission, New Delhi.
- Memmi, J. (2000). Cooking Centralia: a recipe for disaster. Geotimes, Vol. 45(9), pp 26-27.
- Mitchell, T. L. (1839). Three Expeditions into the Interior of Eastern Australia with Descriptions of the Recently Explored Region of Australia Felix and the Present Colony of N.S.W., Vol. 1. Eastern Australia, T. and W. Boone, London, 1938.
- Mukherjee, T.K., Bandopadhyay, T.K. and Pande, S.K. (1991). Detection and delineation of depth of subsurface coalmine fires based on an airborne multispectral scanner survey in a part of the Jharia Coalfield, India, Photogrammetric Engineering and Remote Sensing, Vol. 57, pp. 1203-1207.
- Prakash, A. and Gupta, R.P. (1999). Surface fires in Jharia coalfield, India – their distribution and estimation of area and temperature from TM data, International Journal for Remote Sensing, Vol. 20, No. 10, pp. 1935-1946.
- Prakash, A., Gupta, R.P. and Saraf A.K. (1997). A Landsat TM based comparative study of surface and subsurface fires in the Jharia coalfield, India, International Journal for Remote Sensing, Vol. 18, No. 11, pp. 2463-2469.
- Rattigan, J. H. (1967a). Phenomena about Burning Mountain, Wingen, N.S.W., Australian Journal of Science. 30, 183-184.
- Rattigan, J. H. (1967b). Occurrence and genesis of halloysite, Upper Hunter Valley, N.S.W., Australian Am. Mineral 52, 1795-1805.
- Reddy, C.S.S., Srivastav, S.K. and Bhattacharya, A. (1993). Application of Thematic Mapper short wavelength infrared data for the detection and monitoring of high temperature related geoenvironmental features, International Journal of Remote Sensing, Vol. 14, pp. 3125-3132.
- Rees, W.G. (1990). Physical Principles of Remote Sensing, Cambridge University Press, Cambridge.
- Rosema, A., Guan, H., Veld, H., Vekerdy, Z. Ten Katen, A.M. and Prakash, A. (1999). Manual of Coal Fire Detection and Monitoring, Netherlands Institute of Applied Geosciences.
- Saraf A.K., Prakash, A., Sengupta, S. and Gupta, R.P. (1995). Landsat TM data for estimating ground temperature and depth of subsurface coal fire in the Jharia coalfield, India. International Journal for Remote Sensing, Vol. 16, pp. 2114-2124.
- Schmal, D. (1987). A model for the spontaneous heating of stored coal, Ph.D. Thesis, Technology University of Delft, Delft, The Netherlands.
- Sinha, P.R. (1986). Mine Fires in Indian Coalfields, Energy, Vol. 11(12), pp. 1147-1154.
- Slavecki, R.J. (1964). Detection and location of subsurface coal fires, Proceedings of the Third Symposium on Remote Sensing of Environment, 14th-16th October 1964 (Ann Arbor, Michigan : University of Michigan) pp. 537-547.
- Stracher, G.B. and Taylor, P. T. (2004). Coal fires burning out of control around the world: thermodynamic recipe for environmental catastrophe, International Journal of Coal Geology, Vol. 59, pp. 7-17.
- Tetuko, S.S. J., Tateishi, R. and Takeuchi, N. (2003). A physical method to analyse scattered waves from burnt coal seam and its application to estimate thickness of fire scars in central Borneo using L-Band SAR data, International Journal of Remote Sensing, Vol. 24(15), pp. 3119-3136.
- van der Meer, F.D., van Dijk, P.M., Gangopadhyay, P.K. and Hecker, C.A. (2004). Remote-sensing GIS based investigations of coal fires in northern China: global monitoring to support the estimation of CO2 emissions from spontaneous combustion of coal. In: Proceeding of the 1st Asian Space Conference ASC, held concurrently with the 25th Asian conference on Remote Sensing ACRS : Asian space technology developments and applications and their impacts on culture, commerce and communities : Chiang Mai, Thailand, 22-25 November 2004/ ed. by Vibulresth and D.N. Soo. Geo-Informatics and Space Technology Development Agency GISTDA, 2004. 6 p.
- van Genderen, J.L., Cassells, C.J.S. and Zhang X.M. (1996). The synergisitic use of remotely sensed data for the detection of underground coal fires, International Archives of Phtogrammetry and Remote Sensing, Vol. XXXI, part 7, pp. 722-727.
- Voigt, S., A. Tetzlaff, J. Zhang, C. Künzer, B. Zhukov, G. Strunz, D. Oertel, A. Roth, P. van Dijk and H. Mehl, (2004). Integrating satellite remote sensing techniques for detection and analysis of uncontrolled coal seam fires in North China. International Journal of Coal Geology, vol. 59, p. 121-136.
- Wan, Y.Q. and Zhang X.M. (1996). Using a DEM to reduce the effect of solar heating on Landsat TM thermal IR images and detection of coalfires, Asia-Pacific Remote Sensing and GIS Journal, Vol. 8, pp. 65-72.
- Wang, C. (2002). Detection of coalfires in Xinjiang (China) using remote sensing techniques, MSc Thesis, ITC, Enschede, The Netherlands.
- Xue S. and Winkelmann N., (2005). Detection of underground spontaneous combustion of coal. Proceedings. Coal 2005, Australian Institute of Mining and Metallurgy, Brisbane, 26-28 April, pp.265-267.
- Yang, H. (1995). Detection of Areas of Spontaneous Combustion of Coal Using Airborne and TM Data in Xinxiang, China, MSc Thesis, ITC, Enschede, The Netherlands.
- Zhang X.M., Genderen J.L. van and Kroonenberg S.B. (1997a). A method to evaluate the capability of landsat-5 TM band 6 data for sub-pixel coal fire detection. International Journal of Remote Sensing, 18, pp 3279-3288.
- Zhang, J., Wagner, W., Prakash, A., Mehl, H. and Voigt, S. (2004). Detecting Coal fires using remote sensing techniques, International Journal for Remote Sensing, 25-16, 3193–3220.
- Zhang, J.Z. (1996). SWIR spectra of rocks in areas affected by coalfies, Xinjinag autonomous region P.R. of China, MSc Thesis, ITC, Enschede, The Netherlands.