1. PM source apportionment by Positive Matrix Factorization (PMF) using an extended aerosol chemical characterization including specific molecular markers
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Deepchandra Srivastava, Frédéric Masson, Ngo, S., Antoine Waked, Jean-Luc Jaffrezo, Benjamin Golly, Francony, J. C., Jean-Luc Besombes, Alleman, L. Y., Chabanis, C., Moussu, E., Bret, C., Sophie Tomaz, Emilie Perraudin, Eric VILLENAVE, Nathalie Bocquet, Robin Aujay, Noémie Nuttens, Nadine Guillaumet, Olivier Favez, Alexandre Albinet, Institut National de l'Environnement Industriel et des Risques (INERIS), Laboratoire de Physico -& Toxico Chimie des systèmes naturels (LPTC), Université Sciences et Technologies - Bordeaux 1-Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Chimie Moléculaire et Environnement (LCME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), and Civs, Gestionnaire
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[SDE] Environmental Sciences ,SOURCE APPORTIONMENT ,AIR QUALITY ,[SDE]Environmental Sciences ,MOLECULAR MARKERS ,ORGANIC COMPOUNDS ,POSITIVE MATRIX FACTORIZATION - Abstract
Airborne PM pollution has emerged out as a critical issue all across the world. Quantitative and qualitative source analysis is becoming imperative to imply effective emission control strategies to reduce ambient air pollutants. Receptor oriented models, based on the statistical approach, have been developed to analyze various characteristics of the pollutants measured at the receptor site and to estimate their contributions to the source. Among the multivariate statistical receptor models used for PM source apportionment, Positive Matrix Factorization (PMF) has been adopted world wide as one of the most convenient technique. PMF has a non negative constraint and is able to quantify the factor contribution directly without a subsequent use of multiple regression analysis. More than 40% of European source apportionment studies have applied PMF (Belis et al. 2013). Recent advancements have proposed the use of new organic molecular markers in PMF to better investigate the contribution of biogenic and/or secondary organic aerosols. It has been observed that the use of these compounds improves the efficacy of PM source apportionment (Waked et al. 2014). The main objective of this study was to apportion specific PM10 sources, by using a wide variety of such organic molecular markers as PMF input data, for samples collected at an urban station “Les Frenes” of a local air quality network (Air Rhône-Alpes), considered as representative of a densely populated urban area Grenoble (France). PM10 samples were collected every third day (24 h-basis sampling) on quartz filters over a one year period (2013) and extended chemical characterization was performed including the quantification of species such as OC/EC, ions/cations (Na+, Mg2+, NH4+, Cl-, SO42-, NO3-), Polycyclic Aromatic Hydrocarbon (PAH), oxy-PAH, nitro-PAH, polyols (arabitol, mannitol), Methane Sulfonic Acid (MSA), levoglucosan, sulfur-containing PAH (Benzo[b]naphtha[2,1-d]thiophene, BNT), oxalate, higher odd number alkanes (C27, C29, C31), metals (Ba, Cu, Cr, Zn, Sb, Ni, V, Al, Ti, Fe, Mn, Rb, Ca, K). Results showed that the 10-factor profiles have given the best fit in the PMF analysis including biogenic emissions (marine, soil, plant debris), secondary inorganic (nitrate and sulfate factors) and organic aerosols, dust and aged sea salt particles and anthropogenic sources (oil combustion, traffic exhaust, biomass burning, industry…) (Figure 1). The highest percentage contribution to PM is made by secondary inorganic aerosol (~20%). It is interesting to note that Secondary PAH-aerosol factor accounts for ~ 4%. Discussion will further underline the factor contribution on seasonal basis and the stability of the chosen solution.
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- 2015