Abstract Spontaneous combustion of coal seams is a complicated process that involves complex physical and chemical interactions between the seam and its surrounding environment; the ultimate results are a function of the interplay of internal and external conditions. Based on geologic field investigations and comprehensive analyses, four models of spontaneous combustion for coal were established: (1) a genesis-type model that is based on the coal characteristics that lead to spontaneous combustion; (2) a coal-fires propagation model, namely how spontaneous combustion propagates through a coal seam; (3) a model for the progressive stages and products of a coal fire; and (4) a cross-sectional model of zones that are conducive to spontaneous combustion in a mined-out area. These models provide a scientific and theoretic basis for monitoring and extinguishing the spontaneous combustion of coal.

Abstract Medium-resolution Landsat5 TM (thematic Mapper) and Landsat7 ETM+ (Enhanced thematic Mapper) satellite data were used to investigate multitemporal land-cover changes in the Wuda and Ruqigou-Gulaben coal basins of China between 1987 and 2002. The surficial distribution of coal as detected by remote sensing may be an important indicator of mining activity. Coal that is exposed on the surface may appear as seams in openpit mines; the coal also may occur in storage and waste piles, as refuse at the entrance to a mine, or as coal dust covering areas adjacent to the exposed coal. Because both coal basins are affected by coal fires, monitoring surficial features, including the expansion of coal, is crucial for evaluating the risk for a coal fire. This risk increases where new, often private, mines develop. Remote-sensing data reveal that the increasing number of exposures of coal in the Wuda and Ruqigou-Gulaben coal basins between 1987 and 2002 is correlative with an increase in mining activity there and the associated surficial coal dust adjacent to mining-transport networks. The data also reveal an increase in small-scale private coal mines, especially in the eastern part of the Wuda Coalfield. Such mines often suffer from inadequate mining and environmental regulations and are at high risk for coal fires. Satellite-based detection and in situ verification of new coal fires during field campaigns in 2003 and 2005 confirmed that land-cover analysis is useful for the identification of potential locations for coal fires. The changes that were observed in all other land cover in the Wuda and Ruqigou-Gulaben coal basins represent the more general dominant spatial dynamics in the two regions.

Abstract The study of underground coal fires in China began in the 1960s. The huge loss of coal resources and the ecological disasters caused by coal fires in northern China promoted the study of these fires. Various remote-sensing methods are used to detect ground anomalies due to underground fires. However, locating these fires using remote-sensing data is a difficult task. Ground thermal anomalies are useful for locating underground coal fires. Thermal-geological models link ground thermal anomalies to underground fires. A method of point-source inversion is applicable to a simplified model for the inverse locations of underground coal fires. When tested with data from the Wuda area in the inner Mongolia Autonomous Region of China, this method exhibits encouraging results.

Abstract Remote-sensing imagery is often used for detecting and monitoring coal fires. The Landsat7 Enhanced thematic Mapper Plus (ETM+) sensor and its predecessors of the Landsat family were frequently utilized for that purpose. With Landsat5 quickly approaching the end of its lifetime and the partial malfunction of Landsat7 in 2003, other potential sensors, including Moderate Resolution Imaging Spectrora-diometer (MODIS), merit investigation. One kilometer MODIS data were successfully acquired and analyzed to detect coal fires in China during one summer and two winter night scenes. Band ratios of MODIS bands 20/32 enhanced subpixel-sized hot spots over background values, and an automated thermal anomaly algorithm was an asset in extracting potential coal-fire locations. for areas with known subsurface fires, between 0% and 17% were correctly detected in the three images. Areas with surface fires had success rates of 42% to 49%. These results indicate that MODIS is potentially useful for monitoring large areas for newly developing surface coal fires. Most subsurface coal fires, however, remain undetected.

Abstract Throughout the world, many coal fires are currently burning out of control. In the People’s Republic of China, ∼750 coal fires are burning and depleting a significant amount of the country’s energy supply. Emissions from the smoldering fires are polluting the soil, the groundwater, and the atmosphere. To protect the environment and the natural resources, the Chinese government has taken steps to control or extinguish these fires. In fact, the People’s Republic of China has been fighting these coal fires since the foundation of the country in its present form, following the Chinese fire-fighting manual from 1953. To extinguish a fire—or hot spot, which the fire location is often called—its location must be known with a high degree of accuracy. Hot spots have been successfully located in Xinjiang and inner Mongolia, People’s Republic of China, by combining conventional and modern exploration methods. After the identification of a hot spot, phase terrain and thermal anomalies at the surface are surveyed by using the global positioning system and by thermal mapping with an infrared camera. Subsequently, detailed geological sampling and mapping provide the data to create two- and three-dimensional models of the fire. Our survey results of this initial phase revealed the location of several hot spots. The second phase concentrated on the geophysical survey of selected areas. for instance, magnetic investigations detect thermally demagnetized rocks, geoelectrical surveys measure the resistivity, which tends to increase in burned rocks, and seismo-acoustic surveys “listen to” the fires. As burning coal seams fracture along with the surrounding rock, microtremors are produced. Appropriately placed geophones can detect the source of such tremors. Investigations into coal fires include gas flux measurements and gas analyses to acquire data on air flow, air-flow velocities, and air pollution. By correlating all of the geophysical measurements and integrating them into a combined model, it is possible to determine the location and depth of a hot spot. In addition, the direction and rate of fire propagation can be calculated through interpolation and interpretation of several geophysical measurements. In this study, the results were confirmed by increasing downhole temperature measurements in holes that were drilled into the subsurface.