ASABE Technical Library - Abstract

Click on “Download PDF” for the PDF version or on the title for the HTML version.
If you are not an ASABE member or if your employer has not arranged for access to the full-text, view access and subscription options

Source apportionment of ambient PM2.5 by using Unmix and PMF reception models at Flint Hills rural site and Kansas City urban site

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2016 ASABE Annual International Meeting  162447784.(doi:10.13031/aim.20162447784)
Authors:   Yang Liu, Zifei Liu
Keywords:   CSN, Factor Analysis, IMPROVE, source apportionment, speciated PM2.5.

Abstract. Fine particle PM2.5 has brought air quality concerns in recent years. Source apportionment methods using various reception models have been used to identify the contributing sources of ambient PM2.5. Factor Analysis models were widely used when emission source profiles are not available. Our previous study has successfully unraveled the contribution of prescribed pasture burning at a rural site by using Unmix model. The objectives of this work are to further investigate the contribution of different sources to ambient PM2.5 at both rural and urban sites in Kansas through a comparative analysis using Unmix and PMF reception models. The Unmix and PMF reception models were conducted using 2001-2015 speciated PM2.5 data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network and Chemical Speciation Network (CSN) network at Flint Hills and Kansas City sites, respectively. In Flint Hills site, results from the two models agreed reasonably well on agricultural, industrial, and soil source, both in source composition and contribution to ambient PM2.5. Contribution from secondary aerosol was only identified as an independent source by Unmix model. The secondary aerosol source was encompassed into vegetative burning and industrial sources. In Kansas City site, the secondary organics source included more PM2.5 compositions in PMF model. Single elements dominated sources were identified.

(Download PDF)    (Export to EndNotes)