大气颗粒物源解析受体模型优化技术研究

针对大气颗粒物来源解析技术存在的2大问题:二次有机碳(SOC)对CMB模型的影响及源与受体不匹配程度对源成分谱共线性的影响,给出了解决方案.对于SOC影响的问题,提出从受体的角度扣除SOC,对CMB模型进行修正,降低SOC的影响;对于共线性问题,提出了PCA/MLR-CMB复合模型,复合模型首先进行PCA/MLR的解析,降低受体中未知源的影响,使得纳入CMB模型中的源和受体匹配程度大大提高,从而使得共线性源类能够得到理想的结果.

Improving receptor models for ambient air particulate matter source apportionment

This paper discussed solutions for two of the major technical issues of source apportionment of ambient air particulate matter: the impact of secondary organic carbon (SOC) in the accuracy of CMB modelling; the impact of collinearity problem due to the extent of incompatibility between sources and receptor. For the first issue, the CMB model was modified by deducting SOC from the receptor. For the secondary issue, a PCA/MLR-CMB model was developed. The PCA/MLR-CMB model started with a PCA/MLR appointment, and thus, significantly improved the compatibility between the sources and receptor by reducing of the impact of unknown sources in receptor.