Detection, extinguishing, and monitoring of a coal fire in Xinjiang, China

Two-dimensional inverse problem of fire location in the closed goaf of coal mine based on optical fiber sensors

Monitoring the temperature to determine the fire source locations is essential for controlling the spontaneous combustion in the goaf. Optical fiber sensors are employed to measure the temperature distribution in the goaf. However, due to changes in the geological conditions and the influence of the falling rocks in the goaf, only sensors on the upper side of the uncompacted goaf, due to inclination and coal pillar, may remain. Unilateral sensors are located on the upper side of the goaf, while fire occurs in the center. To investigate the issue with linear unilateral sensors, a two-dimensional inverse method has been developed to determine the location of fire sources by considering heat transfer after a fire inside the goaf. The equations were theoretically solved using Green's function method to obtain the internal temperature distribution of the physical model of the goaf. Sensitivity analysis identified the most crucial parameters in the process of spontaneous heating at different temperature. The fire source location can be determined using a loop method based on the model calculations. We considered a case to validate the model. Accurately identifying the fire source location in the goaf using the unilateral sensors has an essential theoretical and practical significance for fire prevention and fighting.

Detection and management of coal seam outcrop fire in China: a case study

The outcrop fire area in Rujigou Coal Mine in Ningxia, China has been burning continuously for over 100 years. This not only results in wastage of resources but also poses significant damage to the ecological environment. Previous research on open fire detection has mainly focused on coalfield fire areas, using single method such as infrared remote sensing or surface temperature measurement, magnetic method, electrical method, radon measurement and mercurimetry. However, the outcrop fire area has migrated to deeper parts over the years, conventional single fire zone detection methods are not capable of accurately detecting the extent of the fire zone, inversion interpretation is faced with the problem of many solutions. In fire management, current research focuses on the development of new materials, such as fly ash gel, sodium silicate gel, etc., However, it is often difficult to quickly extinguish outcrop fire areas with a single technique. Considering this status quo, unmanned aerial vehicle (UAV) infrared thermal imaging was employed to initially detect the scope of the outcrop fire area, and then both the spontaneous potential and directional drilling methods were adopted for further scope detection in pursuit of more accurate results. In addition, an applicable fire prevention and extinguishing system was constructed, in which three-phase foam was injected for the purpose of absorbing heat and cooling. Furthermore, the composite colloid was used to plug air leakage channels, and loess was backfilled to avoid re-combustion. The comprehensive detection and control technologies proposed in this study can be applied to eliminating the outcrop fire area and protecting the environment. This study can provide guidance and reference for the treatment of other outcrop fire areas.

Near-infrared wide-range dual-gas sensor system for simultaneous detection of methane and carbon monoxide in coal mine environment

To effectively monitor gas explosion and coal spontaneous combustion in coal mine, an intrinsically safe and explosion-proof dual-gas sensor system was developed for methane (CH4) and carbon monoxide (CO) measurement. A distributed feedback (DFB) laser was used to scan two adjacent absorption lines (CH4: 4284.51 cm-1, CO: 4285.01 cm-1). Two measurement ranges of 0-500 parts per million by volume (ppmv) and 0-300,000 ppmv for CH4 and 0-100 ppmv and 0-4000 ppmv for CO were realized using a ∼25 cm single-pass gas cell (SPGC) and a ∼25 m multi-pass gas cell (MPGC), respectively. A gas pre-treatment module was used to remove moisture and aerosols from gas samples. A temperature compensation algorithm was adopted to deal with ambient temperature change. Based on the Allan deviation analysis, the limit of detection (LoD) of CH4 is 0.19 ppmv and the LoD of CO is 0.12 ppmv, respectively, at an averaging time of 0.5 s. A continuous two-day CH4 measurement was performed to demonstrate the long-term stability and environmental monitoring capability. The sensor system was successfully deployed in coal mine gas analysis at Longjiapu, Changchun City, China.

Comprehensive exploration approach of coal mine water-conducting channels in urban environment: a case study in Xintai, China

In the process of coal mining, prevention and control of water hazard is essential. It is the precondition for water hazard control to detect and determine the distribution of underground water-conducting channels. In urban environments, traditional methods such as active source seismic exploration and transient electromagnetic exploration commonly used in the field are difficult to carry out effectively due to various factors. In this paper, the microtremor survey method (MSM) and the opposing coils transient electromagnetic method (OCTEM) are adapted to conduct the surface exploration of the coal mine water-conducting channels in the urban environment. Combined with the detection results of the low-velocity area and the low-resistivity area, the distribution of water-conducting channels is preliminarily analyzed and determined, which is basically consistent with the drilling and coring results. It verifies the feasibility and accuracy of the comprehensive exploration method used in this paper.

Study on the influence of coal fire on the temporal and spatial distribution of CO2 and CH4 gas emissions

In order to study the impact of gas released from coal fire combustion on the spatial-temporal distribution of CO₂ and CH₄ and other greenhouse gas emissions, the impact of regional coal fire on CO₂ and CH₄ emission flux was comprehensively evaluated using Landsat 8 and GOSAT satellite data in Xinjiang. In addition, typical fire areas are selected, a single-channel algorithm is used to invert the surface temperature of the coal field, the spatial distribution of the coal fire area is extracted by setting the threshold, and the influence law of CO₂ and CH₄ emissions in the typical fire area is accurately analyzed. The results show that during 2017-2018, CO₂ and CH₄ emissions in Xinjiang were generally dispersed and locally concentrated, while CO₂-O and CH₄-O were at low levels in most regions, fluctuating in the ranges of 0.01 ~ 0.14 g·m^-2·day^-1 and 0.001 ~ 0.003 g·m^-2·day^-1, respectively. However, the emission intensity of CO₂-O and CH₄-O in coal fire concentrated areas is higher, which are 1.6 ~ 3.8 g·m^-2 day^-1 and 0.013 ~ 0.026 g·m^-2·day^-1, respectively. CO₂-F and CH₄-ag have similar laws. The fire area of Daquan Lake is scattered, and there are four areas with the surface temperature over 35 °C: A, B, C, and D, respectively. The Sandaoba fire area is more concentrated, and only two areas are E and F when the surface temperature exceeds 35 °C. CO₂ and CH₄ released by burning in Daquan Lake and Sandaoba fire areas increased CO₂-F and CH₄-ag by 2.08 and 0.89 times, respectively. The results provide a reference for coal fire control and carbon emission reduction.

Study on the application of coal spontaneous combustion positive pressure beam tube classification monitoring and early warning

To improve the accuracy of early warning on coal spontaneous combustion (CSC), this paper, on the basis of the principle of preferential selection of index gases in CSC process, carries out fitting analysis of the variation curve of index gas data with coal temperature by combining logistic fitting model, then establishes a CSC graded warning system based on positive pressure beam tube monitoring, and determines CO, O₂, φ(CO)/φ(O₂), C₂H₄, C₂H₆, φ(C₂H₄)/φ(C₂H₆) as the index gases for predicting and forecasting CSC, and accurately divides the CSC process into seven levels of early warning: safe, gray, blue, yellow, orange, red, and black. Applying the CSC positive pressure beam tube monitoring system to Dongtan coal mine and analyzing the error by manual sampling and sampling by positive pressure beam tube system, we find that the error is less than 0.1%. Monitoring of several working faces, we get that the CO and CH₄ concentrations of 14,320 working face are higher than the normal level at the beginning of mining, and the 100 × CO/ΔO₂ value is higher than the gray warning threshold of 0.1, and the warning level is gray warning. After taking timely preventive measures against coal oxidation and warming, the CO and CH₄ concentrations return to the normal level and the warning level drops to the safe level. This paper improves the monitoring, identifying and early warning capabilities of underground CSC in its early stage.

Optimization of key parameters for continuous and precise nitrogen injection in goaf based on response surface methodology

In order to solve the problems of coal spontaneous combustion, poor inerting effect of traditional nitrogen injection, and waste of resources in goaf, based on the response surface methodology and Box-Behnken combination test principle, the self-developed continuous and precise nitrogen injection and fire-fighting equipment was used to study the best possible combination of nitrogen injection position (20-90 m), nitrogen injection amount (10-70 m³/min), and air supply volume (2100-2500 m³/min), aiming to minimize the width of the oxidation zone and CO concentration in goaf. The optimal key parameters of continuous precise nitrogen injection were determined as follows: nitrogen injection position 54.17 m, nitrogen injection amount 31.04 m³/min, and air supply 2484.81 m³/min. Under this condition, the width of the oxidation zone was 29.21 ± 0.3 m and the CO concentration was 28.1 ± 4.4 ppm, which were similar to the predicted results of the model (the width of the oxidation zone was 29.41 m; CO concentration was 27.28 ppm). The reliability of the model was verified. These preliminary studies have achieved the purpose of rapid control of the fire in the whole region of the goaf and provided valuable lessons for similar nitrogen injection fire prevention and extinguishing technologies in goaf.

A visual knowledge map analysis of mine fire research based on CiteSpace

Mine fire has always been a serious disaster in coal industry; many academic achievements have poured out in the past two decades for solving this problem. In this study, visual analysis was conducted to grasp the hotspots and development trend of mine fire research. Papers that published in 1999-2020 were retrieved as the data basis from Web of Science, and CiteSpace was used to carry out knowledge map analysis. The results shown that number of papers has increased steadily since 2005 and achieved explosive growth since 2014. Deng J is the first published author among many scholars. China, the USA, and Australia are active areas in mine fire research and China University of Mining and Technology ranks first in this field. The highest co-occurrence frequency keyword is "spontaneous combustion." International Journal of Coal Geology and Fuel provide guidance for mine fire research. Fire prevention technology, low carbon, ecology, and sustainable development are the hot research in recent years. The prevention and control of mine fire from combustion mechanism should be further strengthened.

Effect of high temperatures on the magnetic susceptibility of loess

Coal fires refer to fires generated by the self-combustion of coal seams, which have a maximum temperature of 1000 °C. Such fires can significantly alter the properties of surrounding rock and soil. However, in Northern Shaanxi, China, coal resources are abundant, and the buried depth of coal seams is shallow; therefore, coal fires often occur. Because Northern Shaanxi is located in China's Loess Plateau, there is a large amount of loess accumulation on the surface. For this reason, it is imperative to study the effects of high temperatures on loess. In this paper, the loess samples are heat treated at different temperatures (200-1000 °C), and their surface redness (a*) and mass magnetic susceptibility (χ) are measured to simulate the high-temperature effects of coal fires on the loess in northern Shaanxi, and also study its chromaticity changes and abnormal magnetic properties. The results show that (1) the loess χ value is affected by the heat-treatment temperature; at 600 °C, the χ value decreases, increasing rapidly above after 850 °C. Further, the magnetic susceptibility changes significantly. (2) The thermal-induced transformation of ferromagnetic minerals and the buried depth of loess are the main reasons for these changes in magnetic susceptibility and red chroma of loess.

Spatio-Temporal Characteristics of Air Quality Index (AQI) over Northwest China

In recent years, air pollution has become a serious threat, causing adverse health effects and millions of premature deaths in China. This study examines the spatial-temporal characteristics of ambient air quality in five provinces (Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX), and Qinghai (QH)) of northwest China (NWC) from January 2015 to December 2018. For this purpose, surface-level aerosol pollutants, including particulate matter (PMx, x = 2.5 and 10) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)) were obtained from China National Environmental Monitoring Center (CNEMC). The results showed that fine particulate matter (PM2.5), coarse particulate matter (PM10), SO2, NO2, and CO decreased by 28.2%, 32.7%, 41.9%, 6.2%, and 27.3%, respectively, while O3 increased by 3.96% in NWC during 2018 as compared with 2015. The particulate matter (PM2.5 and PM10) levels exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II standards as well as the WHO recommended Air Quality Guidelines, while SO2 and NO2 complied with the CAAQS Grade II standards in NWC. In addition, the average air quality index (AQI), calculated from ground-based data, improved by 21.3%, the proportion of air quality Class I (0–50) improved by 114.1%, and the number of pollution days decreased by 61.8% in NWC. All the pollutants’ (except ozone) AQI and PM2.5/PM10 ratios showed the highest pollution levels in winter and lowest in summer. AQI was strongly positively correlated with PM2.5, PM10, SO2, NO2, and CO, while negatively correlated with O3. PM10 was the primary pollutant, followed by O3, PM2.5, NO2, CO, and SO2, with different spatial and temporal variations. The proportion of days with PM2.5, PM10, SO2, and CO as the primary pollutants decreased but increased for NO2 and O3. This study provides useful information and a valuable reference for future research on air quality in northwest China.

Multi-Scale Coal Fire Detection Based on an Improved Active Contour Model from Landsat-8 Satellite and UAV Images

Underground coal fires can increase surface temperature, cause surface cracks and collapse, and release poisonous and harmful gases, which significantly harm the ecological environment and humans. Traditional methods of extracting coal fires, such as global threshold, K-mean and active contour model, usually produce many false alarms. Therefore, this paper proposes an improved active contour model by introducing the distinguishing energies of coal fires and others into the traditional active contour model. Taking Urumqi, Xinjiang, China as the research area, coal fires are detected from Landsat-8 satellite and unmanned aerial vehicle (UAV) data. The results show that the proposed method can eliminate many false alarms compared with some traditional methods, and achieve detection of small-area coal fires by referring field survey data. More importantly, the results obtained from UAV data can help identify not only burning coal fires but also potential underground coal fires. This paper provides an efficient method for high-precision coal fire detection and strong technical support for reducing environmental pollution and coal energy use.

Impact of SARS-CoV-2 on Ambient Air Quality in Northwest China (NWC)

SARS-CoV-2 was discovered in Wuhan (Hubei) in late 2019 and covered the globe by March 2020. To prevent the spread of the SARS-CoV-2 outbreak, China imposed a countrywide lockdown that significantly improved the air quality. To investigate the collective effect of SARS-CoV-2 on air quality, we analyzed the ambient air quality in five provinces of northwest China (NWC): Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX) and Qinghai (QH), from January 2019 to December 2020. For this purpose, fine particulate matter (PM2.5), coarse particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were obtained from the China National Environmental Monitoring Center (CNEMC). In 2020, PM2.5, PM10, SO2, NO2, CO, and O3 improved by 2.72%, 5.31%, 7.93%, 8.40%, 8.47%, and 2.15%, respectively, as compared with 2019. The PM2.5 failed to comply in SN and XJ; PM10 failed to comply in SN, XJ, and NX with CAAQS Grade II standards (35 µg/m3, 70 µg/m3, annual mean). In a seasonal variation, all the pollutants experienced significant spatial and temporal distribution, e.g., highest in winter and lowest in summer, except O3. Moreover, the average air quality index (AQI) improved by 4.70%, with the highest improvement in SN followed by QH, GS, XJ, and NX. AQI improved in all seasons; significant improvement occurred in winter (December to February) and spring (March to May) when lockdowns, industrial closure etc. were at their peak. The proportion of air quality Class I improved by 32.14%, and the number of days with PM2.5, SO2, and NO2 as primary pollutants decreased while they increased for PM10, CO, and O3 in 2020. This study indicates a significant association between air quality improvement and the prevalence of SARS-CoV-2 in 2020.

Underground Coal Fire Detection and Monitoring Based on Landsat-8 and Sentinel-1 Data Sets in Miquan Fire Area, XinJiang

Underground coal fires have become a worldwide disaster, which brings serious environmental pollution and massive energy waste. Xinjiang is one of the regions that is seriously affected by the underground coal fires. After years of extinguishing, the underground coal fire areas in Xinjiang have not been significantly reduced yet. To extinguish underground coal fires, it is critical to identify and monitor them. Recently, remote sensing technologies have been showing great potential in coal fires’ identification and monitoring. The thermal infrared technology is usually used to detect thermal anomalies in coal fire areas, and the Differential Synthetic Aperture Radar Interferometry (DInSAR) technology for the detection of coal fires related to ground subsidence. However, non-coal fire thermal anomalies caused by ground objects with low specific heat capacity, and surface subsidence caused by mining and crustal activities have seriously affected the detection accuracy of coal fire areas. To improve coal fires’ detection accuracy by using remote sensing technologies, this study firstly obtains temperature, normalized difference vegetation index (NDVI), and subsidence information based on Landsat8 and Sentinel-1 data, respectively. Then, a multi-source information strength and weakness constraint method (SWCM) is proposed for coal fire identification and analysis. The results show that the proposed SWCM has the highest coal fire identification accuracy among the employed methods. Moreover, it can significantly reduce the commission and omission error caused by non-coal fire-related thermal anomalies and subsidence. Specifically, the commission error is reduced by 70.4% on average, and the omission error is reduced by 30.6%. Based on the results, the spatio-temporal change characteristics of the coal fire areas have been obtained. In addition, it is found that there is a significant negative correlation between the time-series temperature and the subsidence rate of the coal fire areas (R2 reaches 0.82), which indicates the feasibility of using both temperature and subsidence to identify and monitor underground coal fires.

Research on the technology of detection and risk assessment of fire areas in gangue hills

Coal gangue hills are prone to spontaneous combustion, thereby polluting the environment of mining areas such as the soil, groundwater, and atmosphere, and the frequent occurrence of gangue hill collapses, landslides, explosions, and other accidents can even endanger the lives and property of residents. To realize the safety management of coal gangue spontaneous combustion and evaluate its present risks, this paper selects the Dongzhou Kiln gangue hill in Zuoyun County, Datong City, China, as the research object to conduct a risk assessment study. The Dongzhou gangue hill fire area is relatively large, with a total area of 183,039 m². Smoke emission commonly occurs at the site, and the surface temperature reaches 50 °C, while the CO concentration exceeds 10^-3. A radon detection scheme for concealed fire zones verified with borehole temperature measurements is applied. The high-temperature area is delineated with relevant data obtained by infrared thermal imaging, radon concentration, and borehole temperature detection technologies, and a coal gangue spontaneous combustion risk assessment method is established, while the gas toxicity and explosion risks of the construction area and fire trends are analyzed. The research results indicate that there are 6 likely high-temperature regions in the test area, 4 high-toxicity areas in the drilling construction area, 1 area with a high explosion risk, and 3 areas with a high risk of spontaneous combustion. Among these areas, platform 2 is a high-risk area and needs to be carefully considered. The construction of the entire area is at high risk, including toxicity, gas explosion, and spontaneous combustion risks, and measures must be implemented to reduce the overall risk.

Improvement of Foaming Ability of Surfactant Solutions by Water-Soluble Polymers: Experiment and Molecular Dynamics Simulation

Aqueous foam is widely used in fire extinguishing and dust suppression technologies. Improving the foaming ability is the key to reducing the added concentration of foaming agents as well as the economic cost. In this work, the effect of a water-soluble polymer (polyvinyl alcohol, PVA) on the foaming ability of anionic surfactant (sodium dodecyl ether sulfate, SDES) was studied by an experiment and molecular dynamics simulation. The experimental results showed that PVA greatly improves the foaming ability of SDES solutions when the surfactant concentration is less than 0.1%, which is attributed to the fact that the polymer can enhance the stability of bubble films and reduce the bubble rupture rate during the foam generation process. The simulation results indicate that PVA can enhance the hydration of surfactant head groups and contribute to the formation of a three-dimensional hydrogen bond network between surfactants, polymers, and water molecules, thus greatly improving the stability of bubble liquid films. The above results suggest that water-soluble polymers can be used to improve the foaming ability of surfactant solutions by enhancing the bubble film stability, which is beneficial as it reduces the added concentration of foaming agents in aqueous foam applications.

Firefighting of subsurface coal fires with comprehensive techniques for detection and control: a case study of the Fukang coal fire in the Xinjiang region of China

Coal fires are global disasters, and China suffers the most serious coal fire disasters in the world. This paper introduces detailed detection and extinguishing methods for the wide range and complex coal fires at the No. 1 well in the Fukang mining area. First, the characteristics of the large and complex coal fire areas in the No. 1 well in the Fukang mining area are introduced, and 5 large fire areas are detected using the comprehensive detection range method, which detects fire areas before fire engineering practices are implemented. From the characteristics of this large-scale, complex coal fire, the zonal fire extinguishing scheme is formulated, designed, and applied, and the "shallow open fire stripping-construction of the boundary isolation zone-drilling and grouting in the deep fire area" series of events is utilized in the zonal fire extinguishing scheme. A new type of sodium silicate gel in compressive moisturizing plastic packing materials is used, an automatic grouting system is developed, and effective grouting processes are proposed, which can be adjusted according to the grouting effect analysis of the grouting parameters to determine the natural sedimentation and diffusion radius. After the construction was completed, the fire extinguishing effect was tested, revealing that the temperature in the fire zone cooled in a short time, and no subsequent heating phenomenon occurs. The method proposed in this paper provides guidance and a reference for other coal fires in the world.