Assessment of emission-source contribution to spatial dispersion for coal crusher agglomeration using prognostic model

Autor: Amartanshu Srivastava, Suresh Pandian Elumalai
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Cleaner Engineering and Technology, Vol 3, Iss , Pp 100113- (2021)
Druh dokumentu: article
ISSN: 2666-7908
DOI: 10.1016/j.clet.2021.100113
Popis: The emission of inhalable particulates (PM10) from coal comminution processing is detrimental to the air quality. However, limited works have been carried out for the estimation of emission and dispersion of PM10 from coal crushers and its ancillary operations. In this study, field-based measurements and regulatory dispersion model coupled with Weather Research Forecasting (WRF) were applied to investigate the assimilative capacity (AC) of a region with operational coal crushers. The model run was found ‘acceptable’ when compared with measured values according to set performance criteria. Furthermore, the validated model parameterization was used to forecast the dispersion effects by various emission control alternatives recommended by regulators viz. covering of conveyor belts, paving of the unpaved road, reducing feed rate, etc. Results suggested that the major contribution of PM10 was from transportation and loading of coal after crushing, while PM10 levels from crushing dissipated in a smaller area. Paving of transport roads and bunker/silo-based loading were effective control measures as emissions reduced by 30.67%–52.51%. The relationship between distance and emission load revealed that PM10 concentrations below 100 μg/m3 were achieved at approximately 750 m away from emission sources in the present study. Crusher's operations with existing emissions of 23.43 g/day/m2 were detrimental for the region's AC and needed to be stepped down to 11.71 g/day/m2. In particular, using modeled meteorological data provided reasonable forecasts for allowable emissions and planning to site crusher operations. Correction to the low-wind conditions resulted in a better simulation of mean annual estimates than daily estimates of PM10. Such visualization of spatially explicit frameworks will guide policymakers in strengthening regulations.
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