蒙特卡罗不确定性分析在O_3模拟中的初步应用

利用蒙特卡罗不确定性分析方法,分析了嵌套网格空气质量模式系统(NAQPMS/IAP)中154个模式输入变量不确定性对臭氧模拟的影响,量化了模式在北京奥运会期间臭氧模拟的不确定性,并确定出了主要不确定性因子。结果表明:(1)在奥运会期间(2008年8月8日～2008年8月24日),北京城区臭氧模拟的平均不确定性为19ppb,不确定性存在明显的日变化特征,白天不确定性大,夜间不确定性小。(2)在白天,北京城区近地层臭氧模拟最重要的不确定性来源是局地前体物排放,其次是NO2光解系数、风向、北京周边前体物排放和垂直扩散系数。另外,地面约150m以上,对臭氧模拟影响最大的不确定性因子是风向和北京周边前体物排放;夜间,北京城区近地层臭氧模拟的最大不确定性来源是局地NOx排放和垂直扩散系数。

Preliminary Application of Monte Carlo Uncertainty Analysis in O3 Simulation

The Nested Air Quality Prediction Modeling System (NAQPMS) has been applied to the routine air quality forecast in Beijing during the Olympic Games. Monte Carlo method is used to analyze the uncertainty of ozone simulation of NAQPMS during the Olympic Games, from 8 to 24 Aug 2008. Latin hypercube sampling has been used for multi-variables sampling, and 50 ensemble runs have been made with 154 parameter uncertainties being considered together. By the temporal average, the most important parameter to the surface ozone output uncertainty in Beijing is the local precursor emissions during the day time. Other important factors include NO2 photolysis coefficient, wind direction, precursor emissions from the surrounding areas of Beijing, and vertical diffusion coefficient. The wind direction and precursor emissions from the surrounding areas of Beijing have the greatest impact on the uncertainty of daytime ozone simulation at higher levels (above about 150 m). The main uncertainty factors in ozone simulation at night are local NOx emissions and vertical diffusion coefficient. Given the predefined input uncertainties, the average uncertainty of ozone simulation is 19 ppb, ranging from 2 ppb to 49 ppb.