Assessment of spontaneous heating liability of some indian coal by crossing point temperature and Olpinski index method

Abstract

Carbonaceous Organic Aromatic Lump (COAL) is a heterogeneous and stratified Organic rock, formed from decay of vegetable matters or sub-merging forest due to tectonic movement with carbon content varies from 60 to 100%. According to carbon content, Coals are classified in different stages like Peat (50.9%), Lignite (61.8%), Sub-Bituminous (64.5%), Semi-Bituminous (69.5%), Bituminous (78.5%), Anthracite (91%), keeping in view that Graphite (100%) will be the last stage of formation. As the major elemental constituents of coal are Carbon, Hydrogen, Nitrogen, and Oxygen and Sulphur so when these coals are exposed to open-air, it absorbs Oxygen from atmospheric air, liberating heat and ultimately leading to fire. As this liberation of heat is due to the characteristics of Coal, so it is known Spontaneous Heating or Auto-oxidation of Coal or Endogenous Fires which extends during mining. The propensity of this fire is so large noxious gases like CO, CO2, SO2, Nitrous fumes and ultimately, mining activity stops, by blocking up the huge amount of capital and sterilization of reserve [18]. This project deals with the assessment of propensity of different coal samples towards spontaneous heating by assessment of various constraints determined by experimental procedures. The intrinsic properties as well as susceptibility indices of the coal samples have factually been reflected to predict self-heating liability of coal. Four coal samples were collected from MCL (Mahanadi Coalfields Limited) and five from SECL (South Eastern Coalfields Limited), covering some coal fields of India. Liability of collected coal samples were determined using Crossing point temperature and Olpinski index apparatus and the intrinsic properties were determined using proximate analysis method following Indian standards. Based on the results correlation analysis was done among the parameters of proximate analysis and CPT and Sza, also found out the best correlation among them.