Source apportionment of fine PM by combining high time resolution organic and inorganic chemical composition datasets. (July 2019)

• Record Type: Journal Article
• Authors: Belis, C.A.; Pikridas, M.; Lucarelli, F.; Petralia, E.; Cavalli, F.; Calzolai, G.; Berico, M.; Sciare, J.
• Is Part Of: Atmospheric environment. Volume 3(2019)
• Publication Date: 2019-07
• Subjects: Source apportionment -- Particulate matter -- Po valley -- Receptor models -- Positive matrix factorization -- On-line measurements
• DOI: 10.1016/j.aeaoa.2019.100046
• Languages: English
• ISSNs: 2590-1621

Abstract

Abstract: The use of high time resolution datasets of aerosol organic and inorganic species as input for receptor models poses a number of challenges. The estimation of uncertainties differ between different analytical methods and the number of chemical species may considerably vary among the different techniques. In this study, an approach to harmonise the uncertainties of different online datasets for their combined use in source apportionment with positive matrix factorization (PMF) is presented. The concentration of inorganic ions, organic fragments and trace elements were measured in a Po Valley background site using offline and online methods. Six-hour PM2.5 samples were collected on filters and chemical analyses were carried out offline. Parallel hourly online measurements were made using the Xact 625 (CES LLC) XRF analyser and the Q-ACSM (Aerodyne Research Inc.) spectrometer. Online and offline methods produced comparable results for the major chemical component and some trace elements, while others (Ba, Ni, As and Se) showed limited comparability between the two methods. To ensure the consistency of the final PMF results, a multistep approach was adopted. In the first step PMF was run with only the offline dataset, in the second step only the online organic data were used and in a third step the PMF run was executed using only the online inorganic species. In the first three steps running PMF with homogeneous data made it possible to identify the main sources and produce chemical profiles to be used as internal reference for the final fourth step in which all the online species (major inorganic ions, m/z of organic fragments and trace elements) were combined. The sources of the final solution were developed using internally consistent chemical profiles and those from the literature and were validated by analysing the source diurnal variations and by comparison with external tracers. The sources identified were: biomass burning, aged biomass burning, secondary ammonium nitrate and ammonium sulphate, traffic, steel industry and waste thermal treatment. The source profiles with a large set of organic and inorganic species (87) and associated source diurnal variations resulting from this study are expected to serve as reference for future studies. Highlights: High time resolution organic and inorganic data pose challenges for receptor models. Inorganic ions, carbonaceous species and trace elements were measured in N Italy. A multistep approach led to PMF results consistent with off-line and on-line datasets. The combined dataset led to the identification of more sources. Source profiles with 87 species were consistent with external data and literature.