Mining activities contribute the high level of air pollution at ground level and have significant environmental impacts. There is an urge to develop an integrated modeling system which helps to analyze these pollutants and their control strategies. Therefore, a new integrated approach is conceptualized as life cycle based air quality modeling system (LCAQMS) for the mining. This paper focuses on incorporating air quality modeling to understand the severity of air pollution in mining and developing an integrated system for mining related decision support with a field application. The system integrates inverse matrix which is used to develop air emission inventory; characterization method to assess the environmental implications; artificial neural network model for carbon footprint analysis; air dispersion modeling to predict the pollutant concentration at receptor level; and multicriteria decision analysis tool to provide air pollution control solutions. The developed LCAQMS method has applied to a copper mining site in the US. Inventory results reveal that NOX and SO2 produced more as compared to the other pollutants for this site. The study also helps to quantify the carbon credits for the copper mine. Prediction of the four significant pollutants (PM10, PM2.5, SO2, NOx) at ground level have been further calculated and validated with observed values at seven different monitoring stations. The modeling results have supported selecting the best alternative management technology for the air pollution control. It indicates that the developed LCAQMS can serve as a useful tool to assess, predict and assist in the selection of environmental mitigation options for mining sites.

中文翻译：

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用于可持续采矿管理的基于生命周期的空气质量建模和决策支持系统 (LCAQMS)

采矿活动造成了地面高度的空气污染，并对环境产生了重大影响。迫切需要开发一个集成的建模系统，以帮助分析这些污染物及其控制策略。因此，一种新的综合方法被概念化为基于生命周期的采矿空气质量建模系统 (LCAQMS)。本文侧重于结合空气质量模型来了解采矿中空气污染的严重程度，并开发一个用于采矿相关决策支持的集成系统和现场应用。系统集成逆矩阵，用于制定空气排放清单；评估环境影响的表征方法；用于碳足迹分析的人工神经网络模型；空气扩散模型以预测受体水平的污染物浓度；和多标准决策分析工具，以提供空气污染控制解决方案。开发的 LCAQMS 方法已应用于美国的一个铜矿场。清单结果显示，与该地点的其他污染物相比，NOX 和 SO2 产生的更多。该研究还有助于量化铜矿的碳信用额。对地面四种重要污染物（PM10、PM2.5、SO2、NOx）的预测已得到进一步计算，并通过七个不同监测站的观测值进行了验证。建模结果支持为空气污染控制选择最佳替代管理技术。它表明开发的 LCAQMS 可以作为一个有用的工具来评估，