Ozone Sensitivity and Uncertainty Analysis Using DDM-3D in a Photochemical Air Quality Model
Ozone Sensitivity and Uncertainty Analysis Using DDM-3D in a Photochemical Air Quality Model
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在光化学空气质量模型中使用 DDM-3D 进行臭氧敏感性和不确定性分析
DOI：
10.1007/978-1-4615-4153-0_19
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
A. Russell
中科院分区：
文献类型：
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作者：
Yueh;J. Wilkinson;M. Odman;A. Russell
敏感性分析在理解环境系统对模型输入或参数变化的响应方面起着重要作用。这些信息可以进一步用于探索从这些模型输入和参数引入的模型不确定性。然而，敏感性分析由于其复杂性，在多维模型中并没有得到广泛的应用。开发了一种快速、正式的灵敏度技术（DDM-3D），并在CIT （California/Carnegie Institute of Technology）气棚模型中实现，用于评估预测污染物水平对气相光化学机理反应速率常数的灵敏度。这项研究的重点是化学速率常数，在以前的研究中，化学速率常数已被确定为影响预测臭氧不确定性的因素。然后在1987年8月27日至29日应用于南加州洛杉矶地区的多日臭氧事件中计算臭氧对速率参数的敏感性。结果发现，只有有限数量的速率常数对臭氧预测有显著影响。结合灵敏度分析，进行了一阶不确定度分析，结果表明，反应速率常数的不确定度对臭氧水平有显著影响。在下午高臭氧时段，臭氧的不确定性（±lσ）在洛杉矶下风预测水平的10-35%和城市核心的35-50%之间。除了一阶不确定性分析外，还进行了结合拉丁超立方采样（LHS）技术的蒙特卡罗模拟来评估非线性的重要性。结果发现，这两种方法的结果非常相似。结果还表明，臭氧预测的总体不确定性在很大程度上受HNO3生成速率常数的不确定性支配。
Sensitivity analysis plays an important role in understanding the response of an environmental system to the variation of model inputs or parameters. This information can be further utilized to explore the model uncertainties introduced from these model inputs and parameters. However, sensitivity analysis has not been used as widely as desired in multidimensional models because of its complexity. A fast and formal sensitivity technique (DDM-3D) has been developed and implemented in the CIT (California/Carnegie Institute of Technology) airshed model to evaluate the sensitivity of predicted pollutant levels to the reaction rate constants of gas-phase photochemical mechanism. The study focuses on the chemical rate constants, which have been identified to be influential to the predicted ozone uncertainty in previous studies. The ozone sensitivities to rate parameters are then computed spatially in a multiday ozone episode, August 27–29, 1987, applied to the Los Angeles area, southern California. It was found that only a limited number of rate constants have a significant influence on ozone predictions. Combined with the sensitivity analysis, a first-order uncertainty was conducted and results indicate that uncertainty of reaction rate constants have significant impacts on the ozone levels. The uncertainty (± lσ) in ozone ranged from 10–35% of predicted levels downwind of Los Angeles and 35–50% for the urban core during afternoon high-ozone hours. In addition to the first-order uncertainty analysis, a Monte Carlo simulation incorporated with Latin Hypercube Sampling (LHS) technique was conducted to assess the importance of non-linearities. It was found that the two approaches gave very similar results. The results also suggest that the overall uncertainty of predicted ozone is highly dominated by the uncertainty of rate constant of HNO3 formation.