PMF和PCA/APCS模型对南京北郊大气VOCs源解析对比研究

Translated title of the contribution: Comparison of PMF and PCA/APCS for VOCs source apportionment in north suburb of Nanjing

高蒙, 安俊琳*, 杭一纤, 李用宇

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

利用PMF模型和PCA/APCS模型对南京北郊大气VOCs进行定性和定量的源解析,并对比了两种模型的结果。结果表明:PMF模型对不同VOCs种类的模拟效果差别较大,而PCA/APCS对不同VOCs种类的模拟效果相近;PMF模型解析的源个数多于PCA/APCS模型,两种模型结果的源性质方面存在很大相似性,但PCA/APCS模型未能区分汽油挥发和汽车尾气源;两种模型源解析出的植物排放源、工业生产源的贡献率较接近,而其他源的贡献率存在差异,PCA/APCS模型解析的溶剂使用源的贡献率高于PMF模型结果,PMF模型解析出的汽油挥发+汽车尾气源的贡献率高于PCA/APCS模型结果。

The PMF model and PCA/APCS model were used to apportion atmospheric VOCs qualitatively and quantitatively in Nanjing, and both results were compared. The results show that the simulation result for the different types’ VOCs by the PMF model significantly differs, while it is similar to each other by the PCA/APCS model. The number of sources apportioned by the PMF model is greater than that by the PCA/APCS model. Both source profiles are similar, while the PCA/APCS model fails to distinguish gasoline evaporation and vehicle exhaust emission. The contributions of plant emission and industrial production apportioned by the two models are close, while those of the other sources differ. The contribution of solvent use is greater for the PCA/APCS model than for the PMF model, while the contribution of gasoline evaporation plus vehicle exhaust is greater for the PMF model than for the PCA/APCS.
Translated title of the contributionComparison of PMF and PCA/APCS for VOCs source apportionment in north suburb of Nanjing
Original languageChinese (Simplified)
Pages (from-to)43-50
Number of pages8
Journal气象与环境学报
Volume30
Issue number1
DOIs
Publication statusPublished - Feb 2014

User-Defined Keywords

  • VOCs
  • 源解析
  • PMF模型
  • PCA/APCS模型
  • Source apportionment
  • PMF model
  • PCA/APCS model

Fingerprint

Dive into the research topics of 'Comparison of PMF and PCA/APCS for VOCs source apportionment in north suburb of Nanjing'. Together they form a unique fingerprint.

Cite this