Identification of Sources of Phoenix Aerosol by Positive Matrix Factorization

• Published in: Journal of the Air & Waste Management Association (1995) Vol. 50; no. 8; pp. 1308 - 1320
• Main Authors: Ramadan, Ziad, Song, Xin-Hua, Hopke, Philip K.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Pittsburgh, PA Taylor & Francis Group 01.08.2000; Air & Waste Management Association
• Subjects: Aerosols - chemistry; Air Pollution - analysis; Applied sciences; Atmospheric pollution; Earth, ocean, space; Environmental Monitoring - statistics & numerical data; Exact sciences and technology; External geophysics; Factor Analysis, Statistical; Humans; Industry; Meteorology; Models, Statistical; Motor Vehicles; Particle Size; Particles and aerosols; Pollutants physicochemistry study: properties, effects, reactions, transport and distribution; Pollution; United States; North America; Arizona; America; Data analysis; Chemical analysis; Factor analysis; Air quality; Urban area; Coarse particle; Suspended particle; Multicomponent analysis; Surveillance; Fine particle; Factorization method; Content; Positive definite matrix; Aerosols; Pollution source inventory; Air pollution; Chemical composition
• ISSN: 1096-2247; 2162-2906
• DOI: 10.1080/10473289.2000.10464173

Chemical composition data for fine and coarse particles collected in Phoenix, AZ, were analyzed using positive matrix factorization (PMF). The objective was to identify the possible aerosol sources at the sampling site. PMF uses estimates of the error in the data to provide optimum data point scaling and permits a better treatment of missing and below-detection-limit values. It also applies nonnegativity constraints to the factors. Two sets of fine particle samples were collected by different samplers. Each of the resulting fine particle data sets was analyzed separately. For each fine particle data set, eight factors were obtained, identified as (1) biomass burning characterized by high concentrations of organic carbon (OC), elemental carbon (EC), and K; (2) wood burning with high concentrations of Na, K, OC, and EC; (3) motor vehicles with high concentrations of OC and EC; (4) nonferrous smelting process characterized by Cu, Zn, As, and Pb; (5) heavy-duty diesel characterized by high EC, OC, and Mn; (6) sea-salt factor dominated by Na and Cl; (7) soil with high values for Al, Si, Ca, Ti, and Fe; and (8) secondary aerosol with SO 4 -2 and OC that may represent coal-fired power plant emissions. For the coarse particle samples, a five-factor model gave source profiles that are attributed to be (1) sea salt, (2) soil, (3) Fe source/motor vehicle, (4) construction (high Ca), and (5) coal-fired power plant. Regression of the PM mass against the factor scores was performed to estimate the mass contributions of the resolved sources. The major sources for the fine particles were motor vehicles, vegetation burning factors (biomass and wood burning), and coal-fired power plants. These sources contributed most of the fine aerosol mass by emitting carbonaceous particles, and they have higher contributions in winter. For the coarse particles, the major source contributions were soil and construction (high Ca). These sources also peaked in winter.