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Evaluating Dispersion Modeling of Inhalable Particulates (PM_(10)) Emissions in Complex Terrain of Coal Mines

机译:评估煤矿复杂地形中可吸入颗粒的分散模拟(PM_(10))排放

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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 (d(r)) being 0.39, 0.41, and 0.47 for SRTM, ASTER, and CartoDEM, respectively. However, CartoDEM (10 m) showed a slight improvement with d(r) 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 mu g/m(3). 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.
机译:需要精确地鉴定可吸入颗粒(PM10)在露头矿物中的分散,以控制其大气浓度。迄今为止,分散模型中的歪曲地形导致过度/估计的预测。本研究旨在使用Aermod模拟PM10在煤矿中的分散,并评估各种数字高度模型(DEM)所呈现的结果。使用Rational多项式系数方法和公开的DEMS产生的Cardodem(10米),即SRTM(90米),紫砂(30米),布置(30米)和扁平,用于模拟煤矿的复杂地形。将使用不同地形输入预测的建模浓度与用于评估性能度量的场测量值进行比较。与其他输入DEM相比,这种比较建议SRTM和平整地形符合较小的性能标准。使用Willmott的协议索引(D(r))评估模型性能分别为SRTM,Aster和Cardodem的0.39,0.41和0.47。然而,Cardodem(10 m)显示出0.57的D(r)略有改善。结果表明,由于近来的DEM而不是其分辨率,模型性能提高。在所有型号运行的所有型号中,覆盖层倾倒,运输路线和铁路机场在所有型号中都不定于多数PM10浓度负荷,其中峰值浓度从454变化到680μg/ m(3)。分类上,复杂的地形模拟煤矿通过改变排放源与气象数据的预处理器计算的交互影响分散模型。这项工作将有助于提高复杂地形中模型的性能以及基于风险的决策的地形参数化的选择。

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