Inter-comparison of source apportionment models for the estimation of wood burning aerosols during wintertime in an Alpine city (Grenoble, France)

Abstract

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.

The "dual-spot" Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation

“…9b). A similar underestimation of the contribution of wood burning would be observed in Grenoble, France, (Favez et al, 2010), and about a third lower than the actual contribution in Roveredo, Switzerland (Sandradewi et al, 2008b), if non-compensated data had been used for source apportionment of BC. The use of the compensation algorithm greatly improves the calculation of the Ångström exponent.…”

“…A diurnal plot of the biomass burning contribution to BC concentration shows a trend typical for Alpine cities, where wood is used for the residential heating (compare, for example, Favez et al, 2010); there is a large contribution of biomass burning to BC concentration, with a maximum at 32 % during the night (Fig. 9).…”

“…Briefly, the twocomponent model considers the aerosol optical absorption coefficient as a sum of biomass burning and fossil fuel combustion fractions and takes advantage of the difference in the wavelength dependence of absorption: since fossil fuel and biomass contributions to aerosol absorption feature specific values of the absorption Ångström exponent, it is possible to construct a source specific two-component model. We assumed the two sources follow λ −1 and λ −2 spectral dependencies, as used in Sandradewi et al (2008b), and Favez et al (2010), among the range of possible values (Kirchstetter et al, 2004).…”

Comparison of different Aethalometer correction schemes and a reference multi-wavelength absorption technique for ambient aerosol data

“…Moreover, the bulk aerosol wavelength dependence can significantly increase in the presence of other light absorbers, such as BrC (Andreae and Gelencsér, 2006;Kirchstetter et al, 2004), reaching high values between 3.5 and 7.0. Assuming a fixed spectral dependence of 1 for BC, several studies have estimated the BrC contribution as a function of å ABS (Favez et al, 2010;Sandradewi et al, 2008). However, given the uncertainties associated with the å ABS of BC, these methods could potentially provide erroneous BrC estimations (Garg et al, 2016;Schuster et al, 2016a, b;Wang et al, 2016).…”

Black and brown carbon over central Amazonia: Long-term aerosol measurements at the ATTO site

“…Several studies have used the absorption spectral dependence to apportion the fossil fuel and BB contributions to total absorption (Favez et al, 2010;Massabò et al, 2015;Sandradewi et al, 2008). However, the å abs values do not always reflect the combustion type and using it as a source apportionment parameter could lead to erroneous results (Garg et al, 2016;Lewis et al, 2008;Wang et al, 2016b).…”