Application of positive matrix factorization (PMF) to real time aerosol mass spectrometry measurements in an occupied apartment in Sweden

Summary, in English

Introduction
Given that in developed countries we spend about 65% of our time in private homes (Brasche et al. 2005), understanding the exposures in homes is of outmost importance. Airborne particle concentrations indoors can be affected by particles of indoor and outdoor origins, as well as physico-chemical processes indoors, outdoor infiltration affected by tightness of the building envelope and ventilation (Morawska and Salthammer, 2003). In occupied indoor environments, indoor sources may occur simultaneously or as a sequence of the activities. Contribution of airborne particles from different emission sources and various dynamic transformation processes result in 'cocktail effect' in confined indoor spaces. Application of Positive matrix factorization (PMF) source apportionment allows estimating particle contribution from individual sources indoors. The aim of this work was to apply PMF to organic matrix from Aerosol Mass Spectrometer dataset to identify sources contributing to the observed mixture indoors and estimate the relative contributions of organic aerosol types. We present the results of measurements for a three-week period.
Methods
Indoor and outdoor measurements, using automatic switching valve, were performed in an occupied residence in Malmö, Sweden. Time-of-Flight Aerosol Mass Spectrometer (AMS, DeCarlo et al., 2006) was used to measure non-refractory aerosol mass concentrations indoors and outdoors. Positive matrix factorization (PMF) algorithm was applied to indoor organic aerosol dataset for source identification using the bilinear model through a multilinear engine (ME-2). We used graphical user interface SoFi 6.3 H (Source Finder) (Canonaco et. al, 2013) for source apportionment.
Conclusions
Positive matrix factorization source apportionment of the organic aerosol matrix identified three primary factors and one secondary factor: cooking OAI (COAI), cooking OAII (COAII), electronic cigarette OA (EOA), oxygenated outdoor OA (OOA) factors using PMF unconstrained runs. The electronic cigarette was the dominant contributor (51%) to indoor concentrations and resulted in average particle mass concentrations of 5.08 μg m-3. Cooking were frequent events in the studied apartment (n=29). On the basic of the activity logbooks 10 activities were identified as cooking, 6 as baking, 12 as frying, and 1 as deep frying. Cooking activities contributed with average mass concentrations of 3.7 μg m-3 (37 %). Two cooking factors, COAI and COAII, were retrieved during PMF analysis. Both COA factor profiles had characteristic peaks at m/z’s 41, 43, 55, 57, 60, 73 similar to results in previous studies (Allan et al., 2010; Crippa et al., 2013). However, the intensity of m/z’s 60 and 73 of COAI was less pronounced compared to COAII, which can be explained by the presence of degraded sugars during cooking (Barham, 1950). Oxygenated outdoor OA (OOA) factor reflected penetration of oxygenated organic species and was the least pronounced (1.2 μg m-3, 12 %) source indoors. OA mass spectrum was dominated by the CO2+ ion, and formed as a result of decomposition of oxygenated organic acids, as reported earlier by Ng et al. 2010. PMF also enabled identification of unknown sources such as electronic cigarette (by tracing glycerine peak at m/z 61) and some cooking activities.
PMF source apportionment has shown to be useful tool for separation and identification of contributing sources indoors. However, PMF was ineffective for identification of candle burning. Due to similarity of COAI and candle burning mass spectrum, it was decided to proceed with PMF analysis without candle burning profile.
Indoor sources, such as vaping of the electronic cigarette and cooking activities were the main contributors of organic submicrometer-size range particles in studied apartment during the three week measurement period. Thus, these should not be neglected when considering possible health effects.
This work was financed by the Swedish Research Council FORMAS (Project Dnr 942-2015-1029) and COST Action, CA 16109.