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首页> 外文期刊>Journal of Environmental Science and Health. A, Toxic/Hazardous Substances & Environmental Engineering >A Preliminary Study of the Application of Some Predictive Modeling Techniques to Assess Atmospheric Mercury Emissions from Terrestrial Surfaces
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A Preliminary Study of the Application of Some Predictive Modeling Techniques to Assess Atmospheric Mercury Emissions from Terrestrial Surfaces

机译：某些预测建模技术在评估地表大气汞排放中的应用的初步研究

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Predictive modeling techniques are applied to investigate their potential usefulness in providing first order estimates on atmospheric emission flux of gaseous soil mercury and in identifying those parameters most critical in controlling such emissions. Predicted data by simulation and statistical techniques are compared to previously published observational data. Results showed that simulation techniques using air/soil coupling may provide a plausible description of mercury flux trends with a RMSE of 24.4 ng m~(-2) h~(-1) and a mean absolute error of 10.2 ngm~(-2) h~(-1) or 11.9%. From the statistical models, two linear models showed the lowest predictive abilities (R~2 = 0.76 and 0.84, respectively) while the Generalized Additive model showed the closest agreement between estimated and observational data (R~2 = 0.93). Predicted values from a Neural Network model and the Locally Weighted Smoother model showed also very good agreement to measured values of mercury flux (R~2 = 0.92). A Regression Tree model demonstrated also a satisfactory predictability with a value of R~2 = 0.90. Sensitivities and statistical analyses showed that surface soil mercury concentrations, solar radiation and, to a lesser degree, temperature are important parameters in predicting airborne Hg flux from terrestrial soils. These findings are compatible with results from recent experimental studies. Considering the uncertainties associated with mercury cycling and natural emissions, it is concluded, that predictions based on simple modeling techniques seem quite appropriate at present; they can be useful tools in evaluating the role of terrestrial emission sources as part of mercury modeling in local and regional airsheds.
机译：应用预测建模技术研究其潜在用途，以提供气态土壤汞的大气排放通量的一阶估算，并确定对控制此类排放最关键的参数。将通过模拟和统计技术预测的数据与以前发布的观测数据进行比较。结果表明，利用空气/土壤耦合的模拟技术可以提供合理的汞通量趋势描述，其RMSE为24.4 ng m〜（-2）h〜（-1），平均绝对误差为10.2 ngm〜（-2）。 h〜（-1）或11.9％。从统计模型来看，两个线性模型显示出最低的预测能力（分别为R〜2 = 0.76和0.84），而广义加性模型则显示了估计和观测数据之间的最接近一致性（R〜2 = 0.93）。神经网络模型和局部加权平滑器模型的预测值也与汞通量的测量值非常吻合（R〜2 = 0.92）。回归树模型也显示出令人满意的可预测性，R〜2 = 0.90。敏感性和统计分析表明，表层土壤中的汞浓度，太阳辐射以及较低的温度是预测陆生土壤中空气汞通量的重要参数。这些发现与最近的实验研究结果相吻合。考虑到与汞循环和自然排放有关的不确定性，得出的结论是，目前基于简单建模技术的预测似乎相当合适；它们可作为评估陆地排放源在局部和区域气域汞建模中的作用的有用工具。

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