Analysis of air pollution data at a mixed source location using boosted regression trees
Analysis of air pollution data at a mixed source location using boosted regression trees
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DOI：
10.1016/j.atmosenv.2009.04.001
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发表时间：
2009-07-01
影响因子：
5
通讯作者：
Taylor, Paul J.
中科院分区：
文献类型：
--
作者：
Carslaw, David C.;Taylor, Paul J.
本文探讨了使用提升回归树来推断高源复杂性的位置的源特性。建立了一个大型国际机场附近氮氧化物（NOX）的小时浓度模型。模型开发进行了讨论和方法来量化模型的不确定性。结果表明，良好的解释模型，可以开发和进一步，允许模型变量之间的相互作用显着提高了模型拟合与非相互作用的模型相比。方法用于确定哪些变量对预测浓度产生最大影响，并探索每个变量的NOX依赖性。模型预测用于估算飞机起飞对NOx总浓度的贡献，并确定这些预测如何受到气象条件和跑道使用模式的年度变化的影响。此外，飞机对总NOX浓度的贡献的结果进行了比较，从一个更详细的独立的现场活动。最后，我们发现经验证据表明，羽流从较大的飞机分散更迅速地从释放点相比，较小的飞机。这种行为的原因和影响进行了讨论。(C)2009爱思唯尔有限公司保留所有权利。
This paper explores the use of boosted regression trees to draw inferences concerning the source characteristics at a location of high source complexity. Models are developed for hourly concentrations of nitrogen oxides (NOX) close to a large international airport. Model development is discussed and methods to quantify model uncertainties developed. It is shown that good explanatory models can be developed and further, allowing for interactions between model variables significantly improves the model fits compared with non-interacting models. Methods are used to determine which variables exert most influence over predicted concentrations and to explore the NOX dependency for each. Model predictions are used to estimate aircraft take-off contributions to total concentrations of NOX and determine how these predictions are affected by annual variations in meteorological conditions and runway use patterns. Furthermore, the results relating to the aircraft contributions to total NOX concentration are compared with those from a more detailed independent field campaign. Finally, we find empirical evidence that plumes from larger aircraft disperse more rapidly from the point of release compared with smaller aircraft. The reasons for this behaviour and the implications are discussed. (C) 2009 Elsevier Ltd. All rights reserved.