Investigation on Characteristics of Typical Pollutants Generated from Coal Fires: A Case Study of Sulabulak, Xinjiang, China

Coal fires are a significant source of greenhouse gas emissions and ecological pollutants, yet their emission characteristics and carbon accounting remain poorly constrained. To reveal the pollutant generation characteristics and carbon emission levels of the typical underground coal fire area in Sulabulak, Xinjiang, this study integrated laboratory simulation, multi-source remote sensing inversion, and in situ field monitoring. Thermogravimetric analysis, a high-temperature tube furnace, HSC thermodynamic simulation, and multi-source remote sensing data from Landsat-8/9 and Sentinel-1A were employed to investigate the gaseous products and heavy metal migration mechanisms at different combustion stages, and to delineate the spatial extent of different combustion states in the fire area. A coal loss model was then constructed by coupling experimentally determined carbon emission factors with remote sensing-derived areas and was compared with an emission flux model based on field measurements. The results show that the coal oxidation process proceeds through three distinct stages, with indicator gas ratios (CO2/CO and C2H4/C2H6) serving as effective indicators for combustion state identification. Heavy metal partitioning is governed by elemental volatility and redox conditions: As and Se partition predominantly into the gas phase, while Zn becomes enriched in fly ash. Remote sensing time series analysis documents continuous fire expansion accompanied by progressive surface subsidence. By cross-validating the indirect coal loss model (constrained by remote sensing area) against the direct emission flux model (constrained by field measurements), we estimate the current annual GHG emission of the Sulabulak fire area at approximately 0.65 × 104 t CO2 equivalent. This study proposes a coupled “micro-experiment–macro-remote sensing–field measurement” approach for carbon emission accounting, providing reliable data support for environmental pollution control and the development of carbon inventories for coal fires in arid regions.