Source contributions to PM10 and arsenic concentrations in Central Chile using positive matrix factorization

549-561 Sampling of particles (PM10) was conducted during a one-year period at two rural sites in Central Chile, Quillota and Linares. The samples were analyzed for elemental composition. The data sets have undergone source–receptor analyses in order to estimate the sources and their abundanceʹs in the PM10 size fraction, by using the factor analytical method positive matrix factorization (PMF). The analysis showed that PM10 was dominated by soil resuspension at both sites during the summer months, while during winter traffic dominated the particle mass at Quillota and local wood burning dominated the particle mass at Linares. Two copper smelters impacted the Quillota station, and contributed to 10% and 16% of PM10 as an average during summer and winter, respectively. One smelter impacted Linares by 8% and 19% of PM10 in the summer and winter, respectively. For arsenic the two smelters accounted for 87% of the monitored arsenic levels at Quillota and at Linares one smelter contributed with 72% of the measured mass. In comparison with PMF, the use of a dispersion model tended to overestimate the smelter contribution to arsenic levels at both sites. The robustness of the PMF model was tested by using randomly reduced data sets, where 85%, 70%, 50% and 33% of the samples were included. In this way the ability of the model to reconstruct the sources initially found by the original data set could be tested. On average for all sources the relative standard deviation increased from 7% to 25% for the variables identifying the sources, when decreasing the data set from 85% to 33% of the samples, indicating that the solution initially found was very stable to begin with. But it was also noted that sources due to industrial or combustion processes were more sensitive for the size of the data set, compared to the natural sources as local soil and sea spray sources.