Coal fire quantification using ASTER, ETM and BIRD satellite instrument data

Coal fires cause severe environmental and economic problems. Although satellite remote sensing has been used successfully to detect coal fires, a satellite data based concept that can quantify the majority of the detected coal fires is still missing. Recently, the determination of fire radiative energy (FRE) has been introduced as a new remote sensing tool to quantify forest and grassland fires. This thesis tests the concept of remotely measured FRE, with a view to ascertaining its potential applicability to coal fires. It contains an investigation of a new generation of satellite instruments, including the operational Enhanced Thematic Mapper (ETM) instrument, the experimental Bi-spectral InfraRed Detection (BIRD) satellite sensor and the experimental Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which explores the potential of these sensors to determine coal fire radiative energy (CFRE). Additionally, based on the results of this analysis, the thesis presents a new, automated ETM and ASTER data based algorithm, adapted to quantify coal fires in semi-arid to arid regions in northern China. Field observations carried out in September 2002 and 2003 in three coalfields in northern China (the Wuda, Gulaben and Ruqigou coalfields) demonstrate that coal fire related, surface anomalies are significantly cooler than forest and grassland fires. The theoretical investigation of the ASTER, ETM and BIRD instruments outlines the fact that the thermal infrared (TIR) or mid infrared (MIR) spectral channels of the ASTER, ETM and BIRD instrument are particularly effective in registering these ‘warm spots’, whilst the short wave infrared (SWIR) spectral range is, however, insufficiently sensitive to be able to register spectral coal fire radiances. The commonly used bi-spectral fire quantification method (Dozier, 1981) can be applied to BIRD data in order to quantify relatively large and / or hot coal fires. However, existing FRE retrieval approaches fail to quantify coal fires via ASTER and ETM instrument data. In this thesis, a new CFRE retrieval method is presented, which links the fire and background TIR spectral radiances to the CFRE through an empirical relationship. This newly developed TIR method is applied to visually detected fire clusters from night-time ASTER data, and from both day- and night-time ETM data, taken from the three study coalfields in northern China. The ASTER and ETM CFRE values, calculated via the TIR method, are compared to CFRE estimates from BIRD data, calculated via the existing bi-spectral method. Despite the different spatial resolution and spectral properties of the ETM, ASTER and BIRD instruments, CFRE computed from ASTER, ETM and BIRD data show good correlations with one another. However, CFRE retrievals from daytime data appear to be very undependable to background temperature variations, while CFRE, estimated from night-time data, appears to be relatively stable. A comparison between night-time ETM-derived CFRE and the figures given by local mining authorities for total coal fire induced, coal loss estimates in the Wuda coalfield gives a clear indication that the overall dimension of the coal fire problematic can in fact be approximated via satellite data CFRE retrievals. It is thus expected that CFRE derived from night-time satellite data will become a crucial tool in obtaining reliable, quantitative information for coal fires. A multi-temporal comparison of CFRE retrievals from night-time BIRD and ETM data, covering the Ruqigou and Wuda coalfields, indicates that only major shifts or activity changes in coal fire induced, surface anomalies can be observed by means of these data. These results, which could only partially be verified by field observations, indicate that ETM or BIRD data can be used to monitor major changes in coal fire related, surface anomalies. These data however cannot entirely replace detailed field observations, especially in case of smaller and / or cooler coal fire related, surface anomalies

Greenhouse gas emission rate estimates from airborne remote sensing in the short-wave infrared

The quantification of emissions of the greenhouse gases carbon dioxide (CO2) and methane (CH4) is essential for attributing the roles of anthropogenic activity and natural phenomena in global climate change. The current measurement systems and networks, whilst having improved during the last decades, are deficient in many respects. For example, the emissions from localised and point sources such as fossil fuel exploration sites are not readily assessed. A tool developed to better understand point sources of CO2 and CH4 is the optical remote sensing instrument MAMAP, operated from aircraft. With a ground scene size of the order of 50m and a relative accuracy of the column-averaged dry air mole fractions of about 0.3% for XCO2 and less than 0.4% for XCH4, MAMAP can make a significant contribution in this respect. Detailed sensitivity studies showed that the modified WFM-DOAS retrieval algorithm used for MAMAP has an approximate accuracy of about 0.24% for XCH4 and XCO2 in typical atmospheric conditions. At the example of CO2 plumes from two different power plants and CH4 plumes from coal mine ventilation shafts, two inversion approaches to obtain emission rates were developed and tested. One is based on an optimal estimation scheme to fit Gaussian plume models from multiple sources to the data and the other is based on a simple Gaussian integral method. Compared to CO2 emission estimates as reported by the power plants' operator within the framework of emission databases (24 and 13 MtCO2/yr), the results of the individual inversion techniques were within plus/minus 10% with uncertainties of plus/minus 20-30% mainly due to insufficient wind information and non-stationary atmospheric conditions. Measurements at the coal mine included on-site wind observations by an aircraft turbulence probe that could be utilised to calibrate the wind model. In this case, the inversion results have a bias of less than 1% compared to the reported CH4 emissions (50 ktCO2/yr) with an uncertainty of approximately plus/minus 13.5%. In cases where no elevated CO2 or CH4 is observed, MAMAP data are useful to provide upper limit constraints as was shown for a marine gas seep. The inversion techniques developed in this work have the potential to provide the basis for quantification and independent validation of anthropogenic and natural point source emission rates. These concepts are not restricted to airborne applications and are of particular value also for future satellite remote sensing missions

Annual Change Detection by ASTER TIR Data and an Estimation of the Annual Coal Loss and CO2 Emission from Coal Seams Spontaneous Combustion

Coal fires, including both underground and coal waste pile fires, result in large losses of coal resources and emit considerable amounts of greenhouse gases. To estimate the annual intensity of greenhouse gas emissions and the loss of coal resources, estimating the annual loss from fire-influenced coal seams is a feasible approach. This study assumes that the primary cause of coal volume loss is subsurface coal seam fires. The main calculation process is divided into three modules: (1) Coal fire quantity calculations, which use change detection to determine the areas of the different coal fire stages (increase/growth, maintenance/stability and decrease/shrinkage). During every change detections, the amount of coal influenced by fires for these three stages was calculated by multiplying the coal mining residual rate, combustion efficiency, average thickness and average coal intensity. (2) The life cycle estimate is based on remote sensing long-term coal fires monitoring. The life cycles for the three coal fire stages and the corresponding life cycle proportions were calculated; (3) The diurnal burnt rates for different coal fire stages were calculated using the CO2 emission rates from spontaneous combustion experiments, the coal fire life cycle, life cycle proportions. Then, using the fire-influenced quantity aggregated across the different stages, the diurnal burn rates for the different stages and the time spans between the multi-temporal image pairs used for change detection, we estimated the annual coal loss to be 44.3 × 103 tons. After correction using a CH4 emission factor, the CO2 equivalent emissions resulting from these fires was on the order of 92.7 × 103 tons. We also discovered that the centers of these coal fires migrated from deeper to shallower parts of the coal seams or traveled in the direction of the coal seam strike. This trend also agrees with the cause of the majority coal fires: spontaneous combustion of coalmine goafs

Book of abstracts of the 27th Colloquium of African Geology: 17th Conference of the Geological Society of Africa

On behalf of the Local Organizing Committee of “27th Colloquium of African Geology/17th Conference of the Geological Society of Africa – CAG27”, we would like to welcome you to this important meeting regarding “Africa: The key player for a better and sustainable world” that we feel privileged to host. This Conference, sponsored by the Universidade de Aveiro and the GeoBioTec Research Centre, under the auspices of the Geological Society of Africa (GSAf), is an opportunity to continue the scientific exchanges between researchers from all over the world in the field of Geosciences, and to demonstrate the high scientific research standards that are being carried out over the world. The participants in the conference will have the opportunity to share their expertise in a range of scientific fields, such as geology, geological resources, environmental risks, environment and human health, sustainable development, education, and tourism in Africa. (...)publishe

Annual Reports of the Department of the Interior for the fiscal year ended June 30, 1897; Annual Report of the Commissioner of Education, 1897.

Annual Report of the Sec. of Interior. 16 Nov. HD 5, 55-2, v12-22, 8978p. [3640-3650] Indian affairs; annual report of the Gen. Land Office (Serial 3640); annual report of the CIA (Serial 3641); etc