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首页> 外文期刊>Journal of the Air & Waste Management Association >Probability analyses of combining background concentrations with model-predicted concentrations
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Probability analyses of combining background concentrations with model-predicted concentrations

机译:结合背景浓度和模型预测浓度的概率分析

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摘要

In order to calculate total concentrations for comparison to ambient air quality standards, monitored background concentrations are often combined with model predicted concentrations. Models have low skill in predicting the locations or time series of observed concentrations. Further, adding fixed points on the probability distributions of monitored and predicted concentrations is very conservative and not mathematically correct. Simply adding the 99th percentile predicted to the 99th percentile background will not yield the 99th percentile of the combined distributions. Instead, an appropriate distribution can be created by calculating all possible pairwise combinations of the 1-hr daily maximum observed background and daily maximum predicted concentration, from which a 99th percentile total value can be obtained. This paper reviews some techniques commonly used for determining background concentrations and combining modeled and background concentrations. The paper proposes an approach to determine the joint probabilities of occurrence of modeled and background concentrations. The pairwise combinations approach yields a more realistic prediction of total concentrations than the U.S. Environmental Protection Agency's (EPA) guidance approach and agrees with the probabilistic form of the National Ambient Air Quality Standards.
机译:为了计算总浓度以与环境空气质量标准进行比较,通常将监测到的背景浓度与模型预测浓度相结合。模型在预测观察到的浓度的位置或时间序列方面的技能很低。此外,在监测和预测浓度的概率分布上添加固定点非常保守,在数学上也不正确。仅将预测的第99个百分位加到第99个百分位本底,将不会产生组合分布的第99个百分位。取而代之的是,可以通过计算每天1小时最大观察本底值和每日最大预测浓度的所有可能的成对组合来创建适当的分布,从中可以获得第99个百分位数的总值。本文回顾了一些通常用于确定背景浓度以及将建模浓度和背景浓度结合起来的技术。本文提出了一种确定模型浓度和背景浓度发生联合概率的方法。与美国环境保护署(EPA)的指导方法相比,成对组合方法可以更准确地预测总浓度,并且与国家环境空气质量标准的概率形式相一致。

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