CAPPS多箱模式中光化学模式的嵌套与城市大气臭氧数值预报

INTRODUCTION OF A SIMPLIFIED PHOTO-CHEMICAL SCHEME INTO MULTI-BOX MODEL CAPPS FOR URBAN AREA OZONE PREDICTION

为解决城市边界层中大气O3浓度的预报问题 ,选用一种简明有效的光化学反应方案建立光化学模式 ,并与大气平流扩散的箱格预报模型进行了嵌套 ,从而将大气化学过程引入到城市空气污染数值预报系统 (CAPPS)中。同时 ,根据实际需要研究了VOC(VolatileOrganicCompounds)浓度及NOx 源排放量等参数缺测时 ,根据前期监测浓度采用遗传算法反演未知参数的具体方法。利用 2 0 0 1年 9月 8～ 1 7日在北京舞蹈学院监测的O3、NOx 资料及相应的气象数据 ,用改进后的CAPPS模式进行了单箱预报试验。预报试验结果表明 ,嵌套后的模式对O3浓度的变化具备一定的预报能力。

This paper describes the introduction of a photo-chemistry model based on a highly parameterized chemistry mechanism into the nonstatic atmospheric advection-dispersion box-model to practise ozone prediction in urban boundary layer. Genetic algorithm is employed to inverse the VOC (volatile organic compounds) concentration as well as NO x source strength since the ambient pollutant concentration and emission data for urban area are insufficient. This work gives the birth to a new version of the City Air Pollution Prediction System (CAPPS) with the atmospheric chemical processes included. Based on regular sounding data and the pollutant concentration data collected at Beijing Dance Academy, testing predictions of ozone and NO x are performed using the new single-box model. The results indicate that the new model is proved to be an effective tool for urban area ozone prediction.