Journal Article

Source Apportionment of Fine Particulate Matter in Phoenix, AZ, Using Positive Matrix Factorization

Raffuse, Sean M., Anderson, Darcy J., Brown, Steven G., Frankel, Anna, Hafner, Hilary R., Roberts, Paul T.

2007

Overview

Speciated particulate matter (PM) 2.5 data collected as part of the Interagency Monitoring of Protected Visual Environments (IMPROVE) program in Phoenix, AZ, from April 2001 through October 2003 were analyzed using the multivariate receptor model, positive matrix factorization (PMF). Over 250 samples and 24 species were used, including the organic carbon and elemental carbon analytical temperature fractions from the thermal optical reflectance method. A two-step approach was used. First, the species excluding the carbon fractions were used, and initially eight factors were identified; non-soil potassium was calculated and included to better refine the burning factor. Next, the mass associated with the burning factor was removed, and the data set rerun with the carbon fractions. Results were very similar (i.e., within a few percent), but this step enabled a separation of the mobile factor into gasoline and diesel vehicle emissions. The identified factors were burning (on average 2% of the mass), secondary transport (7%), regional power generation (13%), dust (25%), nitrate (9%), industrial As/Pb/Se (2%), Cu/Ni/V (7%), diesel (9%), and general mobile (26%). The overall contribution from mobile sources also increased, as some mass (OC and nitrate) from the nitrate and regional power generation factors were apportioned with the mobile factors. This approach allowed better apportionment of carbon as well as total mass. Additionally, the use of multiple supporting analyses, including air mass trajectories, activity trends, and emission inventory information, helped increase confidence in factor identification.

• Publisher: Taylor & Francis Group,Air & Waste Management Association,Air and Waste Management Association,Taylor & Francis Ltd
• Subject: Air masses / Air Pollutants - analysis / Air quality / Applied sciences / Arizona / Arsenic - analysis / Atmospheric pollution / Carbon / Data analysis / Emission inventories / Emissions (Pollution) / Environmental aspects / Environmental management / Environmental Monitoring - statistics & numerical data / Exact sciences and technology / Factor Analysis, Statistical / Forest & brush fires / Gasoline / Hazardous substances / Ion chromatography / Metallurgy / Metals - analysis / Multivariate Analysis / Nitrates / Nitrates - analysis / Organic carbon / Particles / Particulate matter / Particulate Matter - analysis / Pollution / Power Plants / Soil / Vehicle Emissions