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Evaluating Dispersion Modeling of Inhalable Particulates (PM10) Emissions in Complex Terrain of Coal Mines
The dispersion of inhalable particulates (PM10) in opencast mines needs to be identified precisely for controlling its atmospheric concentration. To date, misrepresented terrains in dispersion models resulted in over/under-estimated predictions. The present study aimed to model the dispersion of PM10 in coal mines using AERMOD and assess outcomes rendered by disparate digital elevation models (DEM). CartoDEM (10 m) generated using the rational polynomial coefficient method and publically available DEMs, i.e., SRTM (90 m), ASTER (30 m), CartoDEM (30 m), and FLAT, were processed for simulating complex terrain of coal mines. Modeled concentration predicted using different terrain inputs was compared with field measured values for evaluating performance metrics. This comparison suggested that SRTM and FLAT topography met lesser performance criteria in comparison with other input DEMs. The model performance was evaluated using Willmott’s index of agreement (dr) being 0.39, 0.41, and 0.47 for SRTM, ASTER, and CartoDEM, respectively. However, CartoDEM (10 m) showed a slight improvement with dr of 0.57. The results revealed that model performance improved due to the recentness of DEM rather than its resolution. Overburden dump, haulage routes, and railway siding shared the majority PM10 concentration load invariably in all model runs where peak concentration varied from 454 to 680 µg/m3. Categorically, complex terrain simulations of coal mines influenced dispersion models by altering emission sources’ interaction with pre-processor calculations of meteorological data. The work will help improve the performance of models in complex terrain and the selection of topographic parameterization for risk-based decisions.
Evaluating Dispersion Modeling of Inhalable Particulates (PM10) Emissions in Complex Terrain of Coal Mines
The dispersion of inhalable particulates (PM10) in opencast mines needs to be identified precisely for controlling its atmospheric concentration. To date, misrepresented terrains in dispersion models resulted in over/under-estimated predictions. The present study aimed to model the dispersion of PM10 in coal mines using AERMOD and assess outcomes rendered by disparate digital elevation models (DEM). CartoDEM (10 m) generated using the rational polynomial coefficient method and publically available DEMs, i.e., SRTM (90 m), ASTER (30 m), CartoDEM (30 m), and FLAT, were processed for simulating complex terrain of coal mines. Modeled concentration predicted using different terrain inputs was compared with field measured values for evaluating performance metrics. This comparison suggested that SRTM and FLAT topography met lesser performance criteria in comparison with other input DEMs. The model performance was evaluated using Willmott’s index of agreement (dr) being 0.39, 0.41, and 0.47 for SRTM, ASTER, and CartoDEM, respectively. However, CartoDEM (10 m) showed a slight improvement with dr of 0.57. The results revealed that model performance improved due to the recentness of DEM rather than its resolution. Overburden dump, haulage routes, and railway siding shared the majority PM10 concentration load invariably in all model runs where peak concentration varied from 454 to 680 µg/m3. Categorically, complex terrain simulations of coal mines influenced dispersion models by altering emission sources’ interaction with pre-processor calculations of meteorological data. The work will help improve the performance of models in complex terrain and the selection of topographic parameterization for risk-based decisions.
Evaluating Dispersion Modeling of Inhalable Particulates (PM10) Emissions in Complex Terrain of Coal Mines
Environ Model Assess
Srivastava, Amartanshu (author) / Kumar, Ambasht (author) / Elumalai, Suresh Pandian (author)
Environmental Modeling & Assessment ; 26 ; 385-403
2021-06-01
19 pages
Article (Journal)
Electronic Resource
English
PM<sub>10</sub> dispersion , AERMOD , Coal mine , OB dump , Air quality , Digital elevation model Environment , Math. Appl. in Environmental Science , Mathematical Modeling and Industrial Mathematics , Operations Research/Decision Theory , Applications of Mathematics , Earth and Environmental Science
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