No abstract

To identify the coarse particle sources and to estimate the variability in their contributions to coarse particle mass (CPM) concentrations across the St. Louis metropolitan area, positive matrix factorization (PMF) was applied to historic ambient coarse particle compositional data from 10 Regional Air Pollution Study/Regional Air Monitoring System (RAPS/RAMS) monitoring sites in St. Louis. Coarse particles in this study had aerodynamic sizes between 2.4 and 20 microm. The sources were qualitatively identified, and the source contributions were quantitatively estimated. Nine sources were identified for 8 of the 10 sampling sites (except rural sites 122 and 124) including soil, cement kiln/quarry, iron and steel, motor vehicle, incinerator, pigment plant primary/secondary lead smelter, zinc smelter, and copper production, respectively. At site 122, five sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, and zinc smelter. At site 124, six sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, primary/secondary lead smelter, and zinc smelter. Soil was the largest coarse particle source across the study area (6.15 microg/m3, 29.3%). Cement kiln/quarry, iron and steel, and motorvehicle sources were the other large contributions to the coarse particles mass (5.27 microg/m3, 25.1%; 3.53 microg/m3, 16.8%; 2.72 microg/m3, 12.9%). The results of this study suggest there can be significant potential for exposure misclassification in time-series epidemiologic studies when regressing health outcomes against source contributions if they were to be estimated at a single central monitoring site.

In this study, the chemical composition of fine particulate matter samples collected at U.S. Environmental Protection Agency Speciation Trends Network sites in San Jose, CA, from February 2000 to February 2005 were analyzed. A San Jose site was initially established at 4th Street and then subsequently moved to Jackson Street in mid-2002. These sites are ϳ1 km apart. There were no known major changes in the nature of the sources in the area over this period. The study used positive matrix factorization model to extract the source profiles and their mass contributions and to compare the results for the congruence of the source apportionments between these two nearby sites. In the case of the 4th Street site, the average mass was apportioned to wood combustion (32.1 Ϯ 2.5%), secondary nitrate (22.3 Ϯ 2%), secondary sulfate (10.7 Ϯ 0.6%), fresh sea salt (7.7 Ϯ 0.9%), gasoline vehicles (7.3 Ϯ 0.5%), aged sea salt (6.8 Ϯ 0.4%), road dust (6.7 Ϯ 0.7%), diesel emissions (3.9 Ϯ 0.3%), and a Ni-related industrial source (2.5 Ϯ 0.4%). At the Jackson Street site, the average mass was apportioned to wood combustion (33.6 Ϯ 2.6%), secondary nitrate (20.3 Ϯ 1.9%), secondary sulfate (13.9 Ϯ 0.9%), aged sea salt (12.4 Ϯ 0.7%), gasoline vehicle (8.3 Ϯ 0.6%), fresh sea salt (5.3 Ϯ 0.5%), diesel emission (3.2 Ϯ 0.3%), road dust (1.9 Ϯ 0.1%), and Ni-related industrial source (1.3 Ϯ 0.1%). Conditional probability function analysis was used to help identify local sources. These results suggested that moving the sampling site a short distance had little effect on the nature of the resolved source types although some differences in their quantitative impacts were obtained in the positive matrix factorization analyses.

Ambient concentrations of PM 10 were measured every fifteen minutes from November 2002 to October 2003 at Alsasua (Northern Spain) using a laser particle counter. A high volume sampler was also used to collect 24-h integrated PM 10 samples at a frequency of three running days per week (i.e. three consecutive PM 10 samples followed by five days without sampling) for gravimetric determination of PM 10 mass concentrations followed by chemical analysis of its chemical components. The annual mean PM 10 concentration obtained using the laser particle counter with gravimetric correction was 22.7 μg m −3 (365 days), while the mean for the gravimetric samples was 29.5 μg m −3 (134 days). A total of 94 integrated PM 10 samples were analyzed for 60 chemical species using a combination of inductively coupled plasma spectrometry (ICP) and ion chromatography (IC). The concentrations of the main PM 10 components were found to be generally in agreement with the values reported for other Spanish cities. Bilinear Positive Matrix Factorization (PMF2) was used to study the sources of PM 10 and its constituents. Six main sources of PM 10 were identified (average contribution to total PM 10 mass in parentheses): crustal material (35%), secondary sulfate (21%), secondary nitrate (14%), motor vehicles (12%), sea-salt aerosol (12%) and metallurgical industries (3%).

and were analyzed to provide source identification and apportionment. A total of 164 samples were collected and 21 species (15 inorganic species, 4 ionic species, OC, and EC) were analyzed by particle-induced x-ray emission, ion chromatography, and thermal optical transmittance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified nine sources and the average mass was apportioned to secondary nitrate (9.3%), motor vehicle (16.6%), road salt (5.8%), industry (4.9%), airborne soil (17.2 %), aged sea salt (6.2%), field burning (6.0%), secondary sulfate (16.2%), and road dust (17.7%), respectively. The nonparametric regression (NPR) analysis was used to help identify local source in the vicinity of the sampling area. These results suggest the possible strategy to maintain and manage the ambient air quality of Seoul.