Open cut black coal mining: Empirical verification of PM2.5 air emission estimation techniques

Abstract

There is a paucity of empirical data relating to PM2.5 emissions from open cut coal mines. Availability of high quality emission data is fundamental to the completion of robust analyses of the potential future impacts of particulate emissions from open cut coal mining operations. This study presents PM2.5 emission rates determined on the basis of empirical data from open cut coal mining operations located in two regions of Australia. These data are used to validate the currently adopted PM2.5 emission estimation methodologies, which are based on total suspended particulate measurements adjusted for PM2.5 size fraction. The emission rates determined in this study demonstrate that regional differences between emission rates may be significant for specific activities. Measured average PM2.5 emission rates are compared to rates calculated using existing available emissions estimation methodologies. This reveals that for dragline operation and coal dumping there are significant differences between the measured emission rates and emission rates calculated using currently available methodologies. This study identifies that the existing adopted US EPA and Australian emissions estimation methods for PM2.5 emissions from coal haul routes, which are one of the most significant sources of PM2.5 emissions at open cut mines, are reliable if the surface moisture content and dust control watering regimes are appropriately accounted for. The Australian estimation method is also considered reliable for overburden haul routes, however the US EPA method over predicts the measured PM2.5 emission rate by a factor of 3.Further, the study highlights that there is a high degree of inherent uncertainty in empirically derived emissions estimates for fugitive dust sources of this type. This uncertainty should be considered when completing emissions calculations, particular where these estimations are subsequently the basis for impact assessment and health risk analysis.