Source apportionment of particulate organic compounds in a rural area of Spain by positive matrix factorization

This study was conducted in order to identify possible sources and to estimate their contribution to particulate matter in a rural area. For this purpose, a commonly used receptor model, positive matrix factorization (PMF), was applied to a PM2.5 data set collected in a rural area of Madrid (Spain) between May 2004 and April 2005. A total of eighty nine samples were gathered. Chemical composition of particulate matter including major components, trace elements, total carbon, alkanes, PAHs, alcohols and acids were analyzed to study sources of atmospheric aerosols using the positive matrix factorization model. This work is characterized by including some organic tracers within PMF analysis, through which we can get a more accurate source apportionment. To our knowledge, this is the first work employing organic tracers for source apportionment by PMF model in a rural area of Spain. To assign PMF factor with a possible source, authors have based on the presence of tracer species. PMF apportioned the PM2.5 mass into nine factors. The factors included (1) even n-alcohols/acids factor, (2) n-alkanes factor, (3) secondary nitrate factor, (4) secondary sulfate factor, (5) secondary organic aerosol, (6) palmitic/stearic factor, (7) PAHs factor, (8) crustal factor and (9) low molecular weight alcohols/acids factor. Six of these factors are related to primary emissions and three of them are categorized as secondary aerosol. PMF identified two mixed sources, factor 6 identified as cooking /microbial source and factor 9 identified as a mixed source. (C) Author(s) 2011. This work is distributed under the Creative Commons Attribution 3.0 License.