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Evaluating Dispersion Modeling of Inhalable Particulates (PM 10 ) Emissions in Complex Terrain of Coal Mines
Environmental Modeling & Assessment ( IF 2.7 ) Pub Date : 2021-03-30 , DOI: 10.1007/s10666-021-09762-w
Amartanshu Srivastava , Ambasht Kumar , Suresh Pandian Elumalai

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.



中文翻译:

煤矿复杂地形中可吸入颗粒物(PM 10)排放的扩散模型评估

需要对露天矿中可吸入颗粒物(PM 10)的分散情况进行精确识别,以控制其大气浓度。迄今为止,在色散模型中错误表示的地形导致过高/过低的预测。本研究旨在模拟PM 10的分散使用AERMOD在煤矿中进行评估,并评估由不同的数字高程模型(DEM)得出的结果。使用有理多项式系数方法生成的CartoDEM(10 m)和SRTM(90 m),ASTER(30 m),CartoDEM(30 m)和FLAT等公开可用的DEM经过处理,以模拟煤矿的复杂地形。将使用不同地形输入预测的模拟浓度与现场测量值进行比较,以评估性能指标。该比较表明,与其他输入DEM相比,SRTM和FLAT地形符合较低的性能标准。使用SRTM,ASTER和CartoDEM的Willmott一致性指数(d r)分别为0.39、0.41和0.47评估了模型性能。但是,CartoDEM(10 m)与d r为0.57。结果表明,由于DEM的最新性而不是其分辨率,模型性能得到了改善。在峰值浓度从454至680 µg / m 3变化的所有模型运​​行中,覆土堆放场,运输路线和铁路侧线始终承担着大部分PM 10浓度负荷。从分类上讲,煤矿的复杂地形模拟通过更改排放源与气象数据的预处理器之间的相互作用来影响扩散模型。这项工作将有助于提高复杂地形中模型的性能,以及选择基于风险决策的地形参数化。

更新日期:2021-03-30
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