Analysis of ambient particle size distributions using Unmix and positive matrix factorization. Kim, E., Hopke, P., K., Larson, T., V., & Covert, D., S. Environmental science & technology, 38(1):202-9, 1, 2004.
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Paper Website abstract bibtex Hourly averaged particle size distributions measured at a centrally located urban site in Seattle were analyzed through the application of bilinear positive matrix factorization (PMF) and Unmix to study underlying size distributions and their daily patterns. A total of 1051 samples each with 16 size intervals from 20 to 400 nm were obtained from a differential mobility particle sizer operating between December 2000 and February 2001. Both PMF and Unmix identify four similar underlying factors in the size distributions. Factor 1 is an accumulation mode particle size spectrum that shows a regular nocturnal pattern, and factor 2 is a larger particle distribution. Factor 3 is assigned as a traffic-related particle distribution, based on its correlations with accompanying gas-phase measurements, and has a regular weekday-high rush-hour pattern. Factor 4 is a traffic-related particle size distribution that has a regular rush-hour pattern on weekdays as well as weekends. Conditional probability functions (CPF) were computed using wind profiles and factor contributions. The results of CPF analysis suggest that these factors are correlated with surrounding particle sources of wood burning, secondary aerosol, diesel emissions, and motor vehicle emissions.
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abstract = {Hourly averaged particle size distributions measured at a centrally located urban site in Seattle were analyzed through the application of bilinear positive matrix factorization (PMF) and Unmix to study underlying size distributions and their daily patterns. A total of 1051 samples each with 16 size intervals from 20 to 400 nm were obtained from a differential mobility particle sizer operating between December 2000 and February 2001. Both PMF and Unmix identify four similar underlying factors in the size distributions. Factor 1 is an accumulation mode particle size spectrum that shows a regular nocturnal pattern, and factor 2 is a larger particle distribution. Factor 3 is assigned as a traffic-related particle distribution, based on its correlations with accompanying gas-phase measurements, and has a regular weekday-high rush-hour pattern. Factor 4 is a traffic-related particle size distribution that has a regular rush-hour pattern on weekdays as well as weekends. Conditional probability functions (CPF) were computed using wind profiles and factor contributions. The results of CPF analysis suggest that these factors are correlated with surrounding particle sources of wood burning, secondary aerosol, diesel emissions, and motor vehicle emissions.},
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author = {Kim, Eugene and Hopke, Philip K and Larson, Timothy V and Covert, David S},
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