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Source apportionment models were widely used to successfully assign highly time-resolved aerosol data to specific emissions and/or atmospheric chemical processes. These techniques are necessary for targeting the sources affecting air quality and for designing effective mitigation strategies. Moreover, evaluation of the toxicity of airborne particulate matter is important since the classically measured particulate matter (PM) concentrations appear insufficient for characterizing the impact on human health. Oxidative potential (OP) measurement has recently been developed to quantify the capability of PM to induce an oxidative imbalance in the lungs. As a result, this measurement unit could be a better proxy than PM mass concentration to represent PM toxicity. In the present study, two source apportionment analyses were performed using positive matrix factorization (PMF) from organic aerosol (OA) mass spectra measured at a 15 min time resolution using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and from 19 trace elements measured on an hourly basis using an online metal analyser (Xact 625i). The field measurements were carried out in summer 2018. While it is common to perform PMF studies individually on ACSMs and more recently on Xact datasets, here we used a two-step methodology leading to a complete PM 1 source apportionment. The outputs from both OA PMF and Xact PMF, the inorganic species concentrations from the ACSM, and the black carbon (BC) fractions (fossil fuel and wood burning) measured using an Aethalometer (AE33) were gathered into a single dataset and subjected to a combined PMF analysis. Overall, eight factors were identified, each of them corresponding to a more precise source than performing single PMF analyses. The results show that besides the high contribution of secondary ammonium sulfate (28 %) and organic nitrate (19 %), about 50 % of PM 1 originated from distinct combustion sources, including emissions from traffic, shipping, industrial activities, cooking, and biomass burning. Simultaneously, PM 1 filters were collected during the experimental period on a 4 h sampling basis. On these filters, two acellular OP assays were performed (dithiothreitol; OP DTT and ascorbic acid; OP AA) and an inversion method was applied on factors issued from all PMFs to assess the contribution of the PM sources to the OP. This work highlights the sensitivity of OP AA to industrial and dust resuspension sources and those of OP DTT to secondary ammonium sulfate, shipping, and biomass burning. [ABSTRACT FROM AUTHOR]

Source apportionment models were widely used and/or atmospheric chemical processes. These technics are necessary to target the sources affecting air quality and to design effective mitigation strategies. More, the evaluation of the toxicity of airborne particulate matter gains interest as the PM concentrations classically measured appear insufficient to characterise the human health impact. Oxidative Potential (OP) measurement have recently been developed to quantify the PM capability to induce an oxidative imbalance in lungs. As a result, this measurement unit could be a better proxy than PM mass concentration to represent PM toxicity. In the present study, two source apportionment analyses were performed using Positive Matrix Factorization (PMF) from organic aerosol (OA) mass spectra measured at 15 min time resolution using a Time of Flight-Aerosol Chemical Speciation Monitor (ToF-ACSM) and from 19 trace elements measured on an hour basis using an online metals analyser (Xact). The field measurements were carried out in summer 2018. While it is common to perform PMF studies individually on ACSM and more recently on Xact datasets, here we used a two-step methodology leading to a complete PM1 source apportionment. The outputs from both OA PMF and Xact PMF, the inorganic species concentrations from the ACSM and the black carbon (BC) fractions (fossil fuel and wood burning) measured using an Aethalometer (AE33) were gathered into a single dataset and subjected to a combined PMF analysis. In overall, 8 factors were identified, each of them corresponding to a more precise source than performing the previous single PMF analyses. The results show that besides the high contribution of secondary ammonium sulfate (28 %) and organic nitrate (19 %), about 50 % of PM1 were originated from combustion processes (traffic, shipping, industrial, cooking and biomass burning emissions). Simultaneously, PM1 filters were collected during the experimental period on a 4 hours sampling basis. On these filters, two acellular OP assays were measured (dithiothreitiol; OPDTT and ascorbic acid; OPAA) and an inversion method is applied on factors issued from all PMFs to assess contributions of the PM sources to the OP. This work highlights the sensitivity of OPAA toward industrial and dust resuspension sources and those of OPDTT toward secondary ammonium sulfate, shipping and biomass burning. [ABSTRACT FROM AUTHOR]

• Development of an analytical method to analyze monosaccharide anhydrides in lichen. • High reliability and validation in lichen test matrix. • First quantification of levoglucosan biomass burning tracer in lichen samples. Lichens are effective atmospheric bioindicators, and the bioaccumulation of pollutants is frequently measured in their tissues to assess contamination levels. Even though monosaccharide anhydrides are not directly considered as contaminants, Levoglucosan is a common tracer of biomass burning in atmospheric samples and measuring their accumulation in lichens could help to evaluate the main atmospheric pollution sources on a spatially resolved scale depending on the size of the sampling grid. In this work, a realiable analytical method to determine monosaccharide anhydrides in liches was developed. It is based on ASE extraction, solid phase extraction to clean the sample, and silylation derivatization before GC/MS analysis. The reliability and detection limits of the method were suited to the analysis of lichen samples, and additional quality tests achieved the validation of the method with lichen test matrix. Finally field samples were quantified and the results obtained were consistent with atmospheric levels. [ABSTRACT FROM AUTHOR]