Source apportionment of fine particulate matter in Phoenix, AZ, using positive matrix factorization

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Air Quality Monitoring

Background:

• Particulate matter (PM2.5) impacts air quality and public health.
• Understanding PM2.5 sources is crucial for effective pollution control strategies.

Purpose of the Study:

• To identify and quantify sources of speciated PM2.5 in Phoenix, AZ.
• To apply the positive matrix factorization (PMF) receptor model for source apportionment.

Main Methods:

• Analysis of speciated PM2.5 data from the IMPROVE program (April 2001-October 2003).
• Utilized a two-step positive matrix factorization (PMF) approach, incorporating carbon fractions and supporting analyses.
• Included air mass trajectories, activity trends, and emission inventory data for validation.

Main Results:

• Identified key PM2.5 sources: burning, secondary transport, regional power generation, dust, nitrate, industrial (As/Pb/Se, Cu/Ni/V), diesel, and general mobile sources.
• Mobile sources (gasoline and diesel) were significant contributors, with their overall contribution increasing after refinement.
• The refined PMF approach improved the apportionment of both carbon and total PM2.5 mass.

Conclusions:

• The study successfully apportioned PM2.5 mass to specific sources in Phoenix.
• Mobile emissions represent a substantial portion of PM2.5 pollution in the study area.
• The applied methodology enhances confidence in source identification and quantification for air quality management.