Long term measurement and source apportionment of non-methane hydrocarbons in three French rural areas

Sauvage, S.; Plaisance, H.; Locoge, N.; Wroblewski, Adam C.; Coddeville, P.; Galloo, J.-C.

doi:10.1016/j.atmosenv.2009.02.001

Cited by 82 publications

(83 citation statements)

References 43 publications

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“…An additional minor continental contribution seems to be associated with the Peloponnese region (Greece -European air masses). As a conclusion, factor 6 can be interpreted as a regional contribution of various remote sources of the Mediterranean region, hence showing the continental regional background (Hellén et al, 2003;Leuchner et al, 2015;Sauvage et al, 2009). These sources were transported towards the receptor site by aged air masses which had not recently been in contact with additional anthropogenic sources.…”

Section: Regional Background (Factor 6)mentioning

confidence: 99%

“…Several base runs with different numbers of factors were performed initially and examined in order to determine the optimal number of factors following the protocol proposed by Sauvage et al (2009). The selection of the optimal solution relies on several statistical indicators and the physical meaning of factor profiles.…”

Section: Optimized Pmf Solutionmentioning

confidence: 99%

“…Some of the computed factors may not be directly related to emission profiles but should rather be interpreted as aged profiles originating from different sources belonging to similar source categories ( Sauvage et al, 2009). PMF was conducted to identify covariation factors of VOCs that were representative of aged or local primary emissions as well as secondary photochemical transformations occurring during the transport of air masses sampled at this background site (Michoud et al, 2017).…”

Section: Source Apportionment Of Vocsmentioning

confidence: 99%

“…Over the last decade, this source receptor approach has been intensively used in urban areas (e.g., Baudic et al, 2016;Salameh et al, 2016;Yuan et al, 2012) and in remote/rural environments Leuchner et al, 2015;Michoud et al, 2017;Sauvage et al, 2009). Other receptor models such as principal component analysis/absolute principal component scores (PCA/APCSs) (Guo et al, 2007), UNMIX (Jorquera and Rappenglück, 2004) and chemical mass balance (CMB) (Badol et al, 2008) have been previously used in VOC source apportionment.…”

Section: Introductionmentioning

confidence: 99%

“…Yuan et al (2012) stressed the importance of the different reactivity of VOCs and the impact of photochemical aging on the interpretability of the resolved factors as source profiles that have not been considered in most of the studies applying PMF. Therefore, in remote/rural environments, despite the assumption of non-reactivity or mass conservation , PMF can be either used to identify aged primary sources or to get insights into the sources and processes involved in the evolution of measured VOCs (Michoud et al, 2017;Sauvage et al, 2009). …”

Section: Introductionmentioning

confidence: 99%

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Origin and variability in volatile organic compounds observed at an Eastern Mediterranean background site (Cyprus)

et al. 2017

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Abstract. More than 7000 atmospheric measurements of over 60 C 2 −C 16 volatile organic compounds (VOCs) were conducted at a background site in Cyprus during a 1-month intensive field campaign held in March 2015. This exhaustive dataset consisted of primary anthropogenic and biogenic VOCs, including a wide range of source-specific tracers, and oxygenated VOCs (with various origins) that were measured online by flame ionization detection-gas chromatography and proton transfer mass spectrometry. Online submicron aerosol chemical composition was performed in parallel using an aerosol mass spectrometer. This study presents the high temporal variability in VOCs and their associated sources. A preliminary analysis of their time series was performed on the basis of independent tracers (NO, CO, black carbon), meteorological data and the clustering of air mass trajectories. Biogenic compounds were mainly attributed to a local origin and showed compound-specific diurnal cycles such as a daily maximum for isoprene and a nighttime maximum for monoterpenes. Anthropogenic VOCs as well as oxygenated VOCs displayed higher mixing ratios under the influence of continental air masses (i.e., western Asia), indicating that long-range transport significantly contributed to the VOC levels in the area. Source apportionment was then conducted on a database of 20 VOCs (or grouped VOCs) using a source receptor model. The positive matrix factorization and concentration field analyses were hence conducted to identify and characterize covariation factors of VOCs that were representative of primary emissions as well as chemical transformation processes. A six-factor PMF solution was selected, namely two primary biogenic factors (relative contribution of 43 % to the total mass of VOCs) for different types of emitting vegetation; three anthropogenic factors (shortlived combustion source, evaporative sources, industrial and evaporative sources; 21 % all together), identified as being either of local origin or from more distant emission zones (i.e., the south coast of Turkey); and a last factor (36 %) associated with regional background pollution (air masses transported both from the Western and Eastern Mediterranean regions). One of the two biogenic and the regional background factors were found to be the largest contributors to the VOC concentrations observed at our sampling site. Finally, a combined analysis of VOC PMF factors with source-apportioned organic aerosols (OAs) helped to better distinguish between anthropogenic and biogenic influences on the aerosol and gas phase compositions. The highest OA concentrations were observed when the site was influenced by air masses rich in Published by Copernicus Publications on behalf of the European Geosciences Union. 11356C. Debevec et al.: Volatile organic compounds at an Eastern Mediterranean background site semi-volatile OA (less oxidized aerosols) originating from the southwest of Asia, in contrast with OA factor contributions associated with the remaining source regions. A reinforcement of sec...

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Section: Regional Background (Factor 6)mentioning

confidence: 99%

Section: Optimized Pmf Solutionmentioning

confidence: 99%