PCA- and PMF-based methodology for air pollution sources identification and apportionment

摘要: Air pollution is a wide concern for human health and requires the development of air quality control strategies. In order to achieve this goal sources have be accurately identified quantified. The case study presented in paper part scientific project initiated by French Ministry Ecology Sustainable Development. For following measurements chemical composition data particles been conducted on french urban site. first step consists identification profiles which achieved through Principal Component Analysis completed rotation technique. Then apportionment evaluated with receptor modeling using Positive Matrix Factorization as estimation method. Finally joint use these two statistical methods enables characterize apportion five different fine particulate emission.