Positive matrix factorization (PMF) analysis of molecular marker measurements to quantify the sources of organic aerosols.

One hundred and twenty five particulate matter samples that were collected over a 2 year period at the St. Louis Midwest Supersite were analyzed for 24 hour average organic carbon (OC), elemental carbon (EC), and particle-phase organic compound (molecular markers) concentrations. Over 100 organic compounds along with measurements of silicon and aluminum were analyzed using a factor analysis based source apportionment model, positive matrix factorization (PMF), which has been widely used in the past with elemental data but not organic molecular markers. Four different solutions (7, 8, 9, and 10 factor solutions) to the PMF model were explored to consider the stability of the source apportionment results, which were found to be reasonably stable. The eight-factor solution was further explored and compared to a parallel chemical mass balance (CMB) source apportionment modeling result that used a subset of the PMF data. A base case eight-factor PMF solution resolved two point source factors, two winter combustion factors, a biomass-burning factor, a mobile source factor, a secondary organic aerosol factor, and a resuspended soil factor. An optimized eight-factor case was also examined, which was formulated by removing three extreme point source impacts observed in the base case, to better understand the nonpoint sources. In the optimized case, the daily OC explained by the biomass burning shows good agreement with the corresponding CMB source, with a slope of 0.93 +/- 0.03. Likewise, the average OC explained by the optimized PMF resuspended soil factor showed good correlation with the CMB road dust apportionment, but there was a significant bias between the two results. The optimized PMF OC from one of the winter combustion factors showed good correlation with the CMB natural gas combustion apportionment but also has a significant bias. In both cases, PMF analysis factored one mobile source controlled by hopanes and streranes, which did not correlate well with any of the three CMB mobile sources. Although the most of the molecular markers were clustered with the PMF model in a manner consistent with prior knowledge of these organic compounds, one significant deviation was observed. Cholesterol, used in the past as a tracer for meat smoke, was found to largely associate with road dust, which raises questions on the suitability of cholesterol as a tracer for meat smoke in the midwestern U.S.