中文摘要：

提出了一种基于大气透过率的机场周边颗粒物质 量浓度预测模型。首先,建立大气透过率与颗粒物质量浓度之间的定量关系；其次,根据气 象要素类型,分析相对湿度和航空排 放物与颗粒物质量浓度之间的相关性及影响规律；然后,通过模糊神经网络将大气透过率、 消光系数与各气象要素相融合,建立了预测模型；最后,使用实测颗粒物质量浓度数据对预 测模型进行了实验验证。结果表明,本文预测模型能较为客观地反映颗粒物质量浓度的变化 ,预测精度较高。

英文摘要：

In the paper,we propose a method for predicting the concentrations of particulates around airports based on the light-transmittance measurement.The mass concentration of particul ates is first derived in terms of the light transmittance.The derivation is further improved with the considerati on of relative humidity and emission components in the civil aviation applications.The prediction of the mass concent rations of particulates around airports is fulfilled through the classic fuzzy n eural network.The mass concentrations of particulates obtained by the proposed method are confirmed by the measured equivalents.The results demonstrate that our method is sufficient for accurately predicting the mass concentrations of particulates aro und airports.Our method is useful for investigating the variations of mass concentrations of particulates with diffe rent particulate sizes.