Abstract. The emission of organic aerosols (OA) in the ambient air by residential wood burning is nowadays a subject of great scientific concern and a growing number of studies aim at apportioning the influence of such emissions on urban air quality. In the present study, results obtained using two commonly-used source apportionment models, i.e., Chemical Mass Balance (CMB, performed with off-line filter measurements) and Positive Matrix Factorization (PMF, applied to Aerosol Mass Spectrometer measurements), as well as using the recently-proposed Aethalometer model (based on the measurement of the aerosol light absorption at different wavelengths) are inter-compared. This work is performed using field data obtained during the winter season (14 to 29 January 2009) at an urban background site of a French Alpine city (Grenoble). Converging results from the different models indicate a major contribution of wood burning organic aerosols (OM wb ) to the ambient aerosol organic fraction, with mean OM wb contributions to total OA Correspondence to: O. Favez (olivier.favez@ineris.fr) of 68%, 61% and 37% for the CMB, the Aethalometer and the AMS-PMF models respectively, during the period when the three modelling studies overlapped (12 days). Quantitative discrepancies might notably be due to the overestimation of OM wb calculated by the CMB due to the loss of semivolatile compounds from sources to receptor site, as well as to the accounting of oxidized primary wood burning organic (OPOA wb ) aerosols within the Oxygenated Organic Aerosol (OOA) PMF-factor. This OOA factor accounts on average for about 50% of total OM, while non-combustion sources contribute to about 25% and 28% of total OM according to the CMB and Aethalometer models respectively. Each model suggests a mean contribution of fossil fuel emissions to total OM of about 10%. A good agreement is also obtained for the source apportionment of elemental carbon (EC) by both the CMB and the Aethalometer models, with fossil fuel emissions representing on average more than 80% of total EC.

Abstract. In this work, the source of ambient particulate matter (PM10) collected over a one-year period at an urban background site in Lens (France) was determined and investigated using a positive matrix factorization receptor model (US EPA PMF v3.0). In addition, a potential source contribution function (PSCF) was performed by means of the Hybrid Single-Particle Lagrangian Integrated Trajectory (Hysplit) v4.9 model to assess prevailing geographical origins of the identified sources. A selective iteration process was followed for the qualification of the more robust and meaningful PMF solution. Components measured and used in the PMF included inorganic and organic species: soluble ionic species, trace elements, elemental carbon (EC), sugar alcohols, sugar anhydride, and organic carbon (OC). The mean PM10 concentration measured from March 2011 to March 2012 was about 21 μg m−3 with typically OM, nitrate and sulfate contributing to most of the mass and accounting respectively for 5.8, 4.5 and 2.3 μg m−3 on a yearly basis. Accordingly, PMF outputs showed that the main emission sources were (in decreasing order of contribution) secondary inorganic aerosols (28% of the total PM10 mass), aged marine emissions (19%), with probably predominant contribution of shipping activities, biomass burning (13%), mineral dust (13%), primary biogenic emissions (9%), fresh sea salts (8%), primary traffic emissions (6%) and heavy oil combustion (4%). Significant temporal variations were observed for most of the identified sources. In particular, biomass burning emissions were negligible in summer but responsible for about 25% of total PM10 and 50% of total OC in wintertime. Conversely, primary biogenic emissions were found to be negligible in winter but to represent about 20% of total PM10 and 40% of total OC in summer. The latter result calls for more investigations of primary biogenic aerosols using source apportionment studies, which quite usually disregard this type of source. This study further underlines the major influence of secondary processes during daily threshold exceedances. Finally, apparent discrepancies that could be generally observed between filter-based studies (such as the present one) and aerosol mass spectrometer-based PMF analyses (organic fractions) are also discussed.

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Marseille, the most important port of the Mediterranean Sea, represents a challenging case study for source apportionment exercises, combining an active photochemistry and multiple emission sources, including fugitive emissions from industrial sources and shipping. This paper presents a Chemical Mass Balance (CMB) approach based on organic markers and metals to apportion the primary sources of organic aerosol in Marseille, with a special focus on industrial emissions. Overall, the CMB model accounts for the major primary anthropogenic sources including motor vehicles, biomass burning and the aggregate emissions from three industrial processes (heavy fuel oil combustion/shipping, coke production and steel manufacturing) as well as some primary biogenic emissions. This source apportionment exercise is well corroborated by ¹⁴C measurements. Primary OC estimated by the CMB accounts on average for 22% of total OC and is dominated by the vehicular emissions that contribute on average for 17% of OC mass concentration (vehicular PM contributes for 17% of PM_2.5). Even though industrial emissions contribute only 2.3% of the total OC (7% of PM_2.5), they are associated with ultrafine particles (Dp<80 nm) and high concentrations of Polycyclic Aromatic Hydrocarbons (PAH) and heavy metals such as Pb, Ni and V. On one hand, given that industrial emissions governed key primary markers, their omission would lead to substantial uncertainties in the CMB analysis performed in areas heavily impacted by such sources, hindering accurate estimation of non-industrial primary sources and secondary sources. On the other hand, being associated with bursts of submicron particles and carcinogenic and mutagenic components such as PAH, these emissions are most likely related with acute ill-health outcomes and should be regulated despite their small contributions to OC. Another important result is the fact that 78% of OC mass cannot be attributed to the major primary sources and, thus, remains un-apportioned. We have consequently critically investigated the uncertainties underlying our CMB apportionments. While we have provided some evidence for photochemical decay of hopanes, this decay does not appear to significantly alter the CMB estimates of the total primary OC. Sampling artifacts and unaccounted primary sources also appear to marginally influence the amount of un-apportioned OC. Therefore, this significant amount of un-apportioned OC is mostly attributed to secondary organic carbon that appears to be the major component of OC during the whole period of study

A comprehensive aerosol characterization was conducted at Marseille during summer, including organic (OC) and elemental carbon (EC), major ionic species, radiocarbon (¹⁴C), water-soluble OC and HULIS (HUmic LIke Substances), elemental composition and primary and secondary organic markers. This paper is the second paper of a two-part series that uses this dataset to investigate the sources of Organic Aerosol (OA). While the first paper investigates the primary sources (El Haddad et al., 2010), this second paper focuses on the secondary fraction of the organic aerosol. <br><br> In the context of overall OC mass balance, primary OC (POC) contributes on average for only 22% and was dominated by vehicular emissions accounting on average for 17% of OC. As a result, 78% of OC mass cannot be attributed to the major primary sources and remains un-apportioned. Radiocarbon measurements suggest that more than 70% of this fraction is of non-fossil origin, assigned predominantly to biogenic secondary organic carbon (BSOC). Therefore, contributions from three traditional BSOC precursors, isoprene, $alpha $-pinene and &beta;-caryophyllene, were considered. These were estimated using the ambient concentrations of Secondary Organic Aerosol (SOA) markers from each precursor and laboratory-derived marker mass fraction factors. <br><br> Secondary organic markers derived from isoprene photo-oxidation (ie: 2-methylglyceric acid and 2-methyltetrols) do not exhibit the same temporal trends. This variability was assigned to the influence of NO_x concentration on their formation pathways and to their potential decay by further processing in the atmosphere. The influence of changes in isoprene chemistry on assessment of isoprene SOC contribution was evaluated explicitly. The results suggest a 60-fold variation between the different estimates computed using different isoprene SOC markers, implying that the available profiles do not reflect the actual isoprene SOC composition observed in Marseille. <br><br> Using the marker-based approach, the aggregate contribution from traditional BSOC was estimated at only 4.2% of total OC and was dominated by α-pinene SOC accounting on average for 3.4% of OC. As a result, these estimates underpredict the inexplicably high loadings of OC. This underestimation can be associated with (1) uncertainties underlying the marker-based approach, (2) presence of other SOC precursors and (3) further processing of fresh SOC, as indicated by organosulfates (RSO₄H) and HUmic LIke Substances (HULIS) measurements

In this work, the source of ambient particulate matter (PM₁₀) collected over a one year period at an urban background site in Lens (France) were determined and investigated using a~Positive Matrix Factorization receptor model (US EPA PMF v3.0). In addition, a Potential Source Contribution Function (PSCF) was performed by means of the Hysplit v4.9 model to assess prevailing geographical origins of the identified sources. A selective iteration process was followed for the qualification of the more robust and meaningful PMF solution. Components measured and used in the PMF include inorganic and organic species: soluble ionic species, trace elements, elemental carbon (EC), sugars alcohols, sugar anhydride, and organic carbon (OC). The mean PM₁₀ concentration measured from March 2011 to March 2012 was about 21 μg m⁻³ with typically OM, nitrate and sulfate contributing to most of the mass and accounting respectively for 5.8, 4.5 and 2.3 μg m⁻³ on a yearly basis. Accordingly, PMF outputs showed that the main emission sources were (in a decreasing order of contribution): secondary inorganic aerosols (28% of the total PM₁₀ mass), aged marine emissions (19%), with probably predominant contribution of shipping activities, biomass burning (13%), mineral dust (13%), primary biogenic emissions (9%), fresh sea salts (8%), primary traffic emissions (6%) and heavy oil combustion (4%). Significant temporal variations were observed for most of the identified sources. In particular, biomass burning emissions were negligible in summer but responsible for about 25% of total PM₁₀ and 50% of total OC at wintertime. Conversely, primary biogenic emissions were found to be negligible in winter but to represent about 20% of total PM₁₀ and 40% of total OC in summer. The latter result calls for more investigations of primary biogenic aerosols using source apportionment studies, which quite usually disregards this type of sources. This study furthermore underlines the major influence of secondary processes during daily threshold exceedances. Finally, apparent discrepancies that could be generally observed between filter-based studies (such as the present one) and Aerosol Mass Spectrometer-based PMF analyses (organic fractions) are also discussed here

Viticultural waste has been widely demonstrated to contain high-added value compounds named the stilbenes. Among them, trans-resveratrol (Rsv) and trans-εviniferin (Vf) are the most abundant in particular in grape canes. Various emerging methods such as ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE) or pressurized solvent extraction (PSE) have been studied to recover Rsv and Vf from grape canes in order to enhance their extraction. This paper gives a critical overview of the techniques used to this end, integrating conventional and nonconventional methods investigated in the literature as well as those used in industrial processes. It finally highlights that the unconventional technics are usually less timeconsuming than conventional extraction ones but further investigations for the discussed compounds and biomass are needed to optimize and understand the influence of the individual parameters of each extraction process.

Abstract. The emission of organic aerosols (OA) in the ambient air by residential wood burning is nowadays a subject of great scientific concern and a growing number of studies aim at apportioning the influence of such emissions on urban air quality. In the present study, results obtained using two commonly-used source apportionment models, i.e., Chemical Mass Balance (CMB, performed with off-line filter measurements) and Positive Matrix Factorization (PMF, applied to aerosol mass spectrometer measurements), as well as using the recently-proposed aethalometer model (based on the measurement of the aerosol light absorption at different wavelengths) are inter-compared. This work is performed using field data obtained during the winter season (14 to 30 January 2009) at an urban background site of a French Alpine city (Grenoble). Converging results from the different models indicate a major contribution of wood burning organic aerosols (OMwb) to the organic fraction, with mean OMwb contributions to total OA of about 67%, 60% and 38% for the CMB, the aethalometer and the AMS-PMF models, respectively. Quantitative discrepancies might notably be due to the overestimation of OMwb calculated by the CMB due to the loss of semi-volatile compounds from sources to receptor site, as well as to the accounting of oxidized primary wood burning organic (OPOAwb) aerosols within the Oxygenated Organic Aerosol (OOA) PMF-factor. This OOA factor accounts on average for about 50% of total OM, while non-combustion sources contribute to about 25% and 28% of total OM according to the CMB and aethalometer models, respectively. Each model suggests a mean contribution of fossil fuel emissions to total OM of about 10%. A good agreement is also obtained for the source apportionment of elemental carbon (EC) by both the CMB and aethalometer models, with fossil fuel emissions representing on average more than 80% of total EC.