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Modelling the decay of concentrations of nitrogenous compounds with distance from roads

机译:模拟含氮化合物的浓度随道路距离的衰减

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Passive sampler concentration measurements of nitrogen dioxide (NO_2) and ammonia (NH_3) were performed in the framework of a transect study to investigate the impact of vehicle emissions on ecosystems dissected by highways. The concentrations of both gases decrease markedly with distance from highway to regional background pollution values. Modelling the functional form of the decay is of interest for reducing the amount of measurements, for exposure assessment, and for predicting background concentrations. Three modelling approaches are compared: the exponential decay function, the shifted power-law function, and the linear-logarithmic function. The models were fitted to four compound- and year-specific data sets from one transect, applying mixed-effects models for repeated-measurement designs. The goodness-of-fit did not differ consistently between the model classes. Combined data from four transects with different characteristics were analysed with the exponential decay model, allowing for transect-specific random coefficients. From the empirical point of view, none of the three model classes is consistently superior to the others. But for prediction beyond the observed distance range it is essential to consider a model with meaningful parameters. The final choice of a model depends on the amount of data and on the characteristics to be represented by the model.
机译:在样带研究的框架内,对二氧化氮(NO_2)和氨气(NH_3)进行了被动采样器浓度测量,以研究车辆排放物对公路分离的生态系统的影响。两种气体的浓度随着从公路到区域背景污染值的距离而显着降低。对衰减的功能形式进行建模对于减少测量数量,进行暴露评估以及预测背景浓度非常有用。比较了三种建模方法:指数衰减函数,位移幂律函数和线性对数函数。将该模型拟合到来自一个样带的四个特定化合物和特定年份的数据集,将混合效应模型应用于重复测量设计。拟合优度在模型类之间没有一致的差异。使用指数衰减模型分析了具有不同特征的四个样条的组合数据,从而获得了样条特定的随机系数。从经验的角度来看,这三个模型类别均没有一个始终优于其他三个模型类别。但是对于超出观察距离范围的预测,必须考虑具有有意义参数的模型。模型的最终选择取决于数据量和模型所代表的特征。

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