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

2010 ◽  
Vol 10 (1) ◽  
pp. 559-613 ◽  
Author(s):  
O. Favez ◽  
I. El Haddad ◽  
C. Piot ◽  
A. Boréave ◽  
E. Abidi ◽  
...  

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.

2010 ◽  
Vol 10 (12) ◽  
pp. 5295-5314 ◽  
Author(s):  
O. Favez ◽  
I. El Haddad ◽  
C. Piot ◽  
A. Boréave ◽  
E. Abidi ◽  
...  

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 (OMwb) to the ambient aerosol organic fraction, with mean OMwb contributions to total OA 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 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 the Aethalometer models, with fossil fuel emissions representing on average more than 80% of total EC.


2019 ◽  
Vol 19 (24) ◽  
pp. 15247-15270 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  

Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.


Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 330 ◽  
Author(s):  
Manousos Ioannis Manousakas ◽  
Kalliopi Florou ◽  
Spyros N. Pandis

Fine particulate matter (PM) originates from various emission sources and physicochemical processes. Quantification of the sources of PM is an important step during the planning of efficient mitigation strategies and the investigation of the potential risks to human health. Usually, source apportionment studies focus either on the organic or on the inorganic fraction of PM. In this study that took place in Patras, Greece, we address both PM fractions by combining measurements from a range of on- and off-line techniques, including elemental composition, organic and elemental carbon (OC and EC) measurements, and high-resolution Aerosol Mass Spectrometry (AMS) from different techniques. Six fine PM2.5 sources were identified based on the off-line measurements: secondary sulfate (34%), biomass burning (15%), exhaust traffic emissions (13%), nonexhaust traffic emissions (12%), mineral dust (10%), and sea salt (5%). The analysis of the AMS spectra quantified five factors: two oxygenated organic aerosols (OOA) factors (an OOA and a marine-related OOA, 52% of the total organic aerosols (OA)), cooking OA (COA, 11%) and two biomass burning OA (BBOA-I and BBOA-II, 37% in total) factors. The results of the two methods were synthesized, showcasing the complementarity of the two methodologies for fine PM source identification. The synthesis suggests that the contribution of biomass burning is quite robust, but that the exhaust traffic emissions are not due to local sources and may also include secondary OA from other sources.


2019 ◽  
Vol 19 (17) ◽  
pp. 11235-11252 ◽  
Author(s):  
Alice Corina Forello ◽  
Vera Bernardoni ◽  
Giulia Calzolai ◽  
Franco Lucarelli ◽  
Dario Massabò ◽  
...  

Abstract. In this paper, a new methodology coupling aerosol optical and chemical parameters in the same source apportionment study is reported. In addition to results on source contributions, this approach provides information such as estimates for the atmospheric absorption Ångström exponent (α) of the sources and mass absorption cross sections (MACs) for fossil fuel emissions at different wavelengths. A multi-time resolution source apportionment study using the Multilinear Engine (ME-2) was performed on a PM10 dataset with different time resolutions (24, 12, and 1 h) collected during two different seasons in Milan (Italy) in 2016. Samples were optically analysed by an in-house polar photometer to retrieve the aerosol absorption coefficient bap (in Mm−1) at four wavelengths (λ=405, 532, 635, and 780 nm) and were chemically characterized for elements, ions, levoglucosan, and carbonaceous components. The dataset joining chemically speciated and optical data was the input for the multi-time resolution receptor model; this approach was proven to strengthen the identification of sources, thus being particularly useful when important chemical markers (e.g. levoglucosan, elemental carbon) are not available. The final solution consisted of eight factors (nitrate, sulfate, resuspended dust, biomass burning, construction works, traffic, industry, aged sea salt); the implemented constraints led to a better physical description of factors and the bootstrap analysis supported the goodness of the solution. As for bap apportionment, consistent with what was expected, biomass burning and traffic were the main contributors to aerosol absorption in the atmosphere. A relevant feature of the approach proposed in this work is the possibility of retrieving a lot of other information about optical parameters; for example, in contrast to the more traditional approach used by optical source apportionment models, here we obtained source-dependent α values without any a priori assumption (α biomass burning =1.83 and α fossil fuels =0.80). In addition, the MACs estimated for fossil fuel emissions were consistent with literature values. It is worth noting that the approach presented here can also be applied using more common receptor models (e.g. EPA PMF instead of multi-time resolution ME-2) if the dataset comprises variables with the same time resolution as well as optical data retrieved by widespread instrumentation (e.g. an Aethalometer instead of in-house instrumentation).


2013 ◽  
Vol 13 (2) ◽  
pp. 961-981 ◽  
Author(s):  
M. Crippa ◽  
P. F. DeCarlo ◽  
J. G. Slowik ◽  
C. Mohr ◽  
M. F. Heringa ◽  
...  

Abstract. The effect of a post-industrial megacity on local and regional air quality was assessed via a month-long field measurement campaign in the Paris metropolitan area during winter 2010. Here we present source apportionment results from three aerosol mass spectrometers and two aethalometers deployed at three measurement stations within the Paris region. Submicron aerosol composition is dominated by the organic fraction (30–36%) and nitrate (28–29%), with lower contributions from sulfate (14–16%), ammonium (12–14%) and black carbon (7–13%). Organic source apportionment was performed using positive matrix factorization, resulting in a set of organic factors corresponding both to primary emission sources and secondary production. The dominant primary sources are traffic (11–15% of organic mass), biomass burning (13–15%) and cooking (up to 35% during meal hours). Secondary organic aerosol contributes more than 50% to the total organic mass and includes a highly oxidized factor from indeterminate and/or diverse sources and a less oxidized factor related to wood burning emissions. Black carbon was apportioned to traffic and wood burning sources using a model based on wavelength-dependent light absorption of these two combustion sources. The time series of organic and black carbon factors from related sources were strongly correlated. The similarities in aerosol composition, total mass and temporal variation between the three sites suggest that particulate pollution in Paris is dominated by regional factors, and that the emissions from Paris itself have a relatively low impact on its surroundings.


2020 ◽  
Author(s):  
Aki Virkkula

Abstract. The Aethalometer model been used widely for estimating the contributions of fossil fuel emissions and biomass burning to equivalent black carbon (eBC). The calculation is based on measured absorption Ångström exponents (αabs). The interpretation αabs is ambiguous since it is well-known that it not only depends on the dominant absorber but also on the size and internal structure of the particles, core size and shell thickness. In this work the uncertainties of the Aethalometer-model-derived apparent fractions of absorption by eBC from fossil fuel and biomass burning are evaluated with a core-shell Mie model. Biomass-burning fractions (BB(%)) were calculated for pure and coated single BC particles, for lognormal unimodal and bimodal size distributions of BC cores coated with ammonium sulfate, a scattering-only material. BB(%) was very seldom 0 % even though BC was the only absorbing material in the simulations. The shape of size distribution plays an important role. Narrow size distributions result in higher αabs and BB(%) values than wide size distributions. The sensitivity of αabs and BB(%) to variations in shell volume fractions is the highest for accumulation mode particles. This is important because that is where the largest aerosol mass is. For the interpretation of absorption Ångström exponents it would be very good to measure BC size distributions and shell thicknesses together with the wavelength dependency of absorption.


1970 ◽  
Vol 8 (3) ◽  
pp. 25-31 ◽  
Author(s):  
Injo Hwang

To manage ambient air quality and establish effective emissions reduction strategies, it is necessary to identify sources and to apportion the ambient PM mass. To do so, receptor models have been developed that analyze various measured properties of the pollutants at the receptor site, identify the sources, and estimate their contributions. Receptor modeling is based on a mathematical model that analyzes the physicochemical properties of gaseous and/or particulate pollutants at various atmospheric receptors. Among the multivariate receptor models used for PM source identification and apportionment, positive matrix factorization (PMF) has been developed by Paatero in 1997. PMF have been developed for providing a new approach to multivariate receptor modeling based on explicit least-squares technique. Also, PMF shown to be a powerful technique relative to traditional multivariate receptor models. PMF has been implemented in two different algorithms: PMF2 (or PMF3) and the multilinear engine (ME). Since the release of PMF2 and ME, these programs have been successfully applied to assess ambient PM source contributions at many locations in the world. In this study, I would like to introduce about outline of the PMF model and application of the PMF model to estimate the source apportionment of ambient PM2.5 at various sampling sites in USA and Korea. This study suggests the possible role for maintain and manage ambient air quality and achieve reasonable air pollution strategies. DOI: http://dx.doi.org/10.3126/jie.v8i3.5928 JIE 2011; 8(3): 25-31


Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 385 ◽  
Author(s):  
Luminiţa Mărmureanu ◽  
Jeni Vasilescu ◽  
Jay Slowik ◽  
André S. H. Prévôt ◽  
Cristina Antonia Marin ◽  
...  

Aerosols and organic source apportionment were characterized using data collected during two measurement campaigns. These campaigns were conducted during the summer and winter seasons at Măgurele, a site located southwest of Bucharest, the capital of Romania and one of the largest cities in southeastern Europe (raking seven in Europe based on population). The summer campaign was conducted between 7 June–18 July 2012, and the winter campaign from 14 January–6 February 2013. Approximately 50% of the organic fraction contribution to the total submicron particulate matter sampled by aerosol mass spectrometer was evidenced during both seasons. Submicronic organic aerosol sources were quantified using the positive matrix factorization approach. For warm (summer) and cold (winter) seasons, more than 50% from total organics was represented by oxidized factors. For the summer season, separate analyses were conducted on data influenced by urban and non-urban sources. The influence of pollution from Bucharest on the measurement site was observed in aerosol concentration and composition. The primary organic aerosols have different contribution percentage during summer, depending on their main origin. The influence of Bucharest, during summer, included cooking contribution of 13%. The periods with more regional influence were characterized by lower contribution from traffic and biomass burning in a total proportion of 28%. In winter, the influence of local non-traffic sources was dominant. For more than 99% of the measurements, the biomass burning indicator, f 60 , exceeded the background value, with residential heating being an important source in this area. Fossil fuel contribution was confirmed for one week during the winter campaign, when 14 C analysis of total and elemental carbon revealed the presence of 17% fossil contributions to total carbon. Mass spectrometry, 14 C and absorption data suggest biomass burning as the predominant primary source of organic aerosols for the winter season.


Author(s):  
Steven G. Brown ◽  
Janice Lam Snyder ◽  
Michael C. McCarthy ◽  
Nathan R. Pavlovic ◽  
Stephen D’Andrea ◽  
...  

Ambient air monitoring and phone survey data were collected in three environmental justice (EJ) and three non-EJ communities in Sacramento County during winter 2016–2017 to understand the differences in air toxics and in wood smoke pollution among communities. Concentrations of six hazardous air pollutants (HAPs) and black carbon (BC) from fossil fuel (BCff) were significantly higher at EJ communities versus non-EJ communities. BC from wood burning (BCwb) was significantly higher at non-EJ communities. Correlation analysis indicated that the six HAPs were predominantly from fossil fuel combustion sources, not from wood burning. The HAPs were moderately variable across sites (coefficient of divergence (COD) range of 0.07 for carbon tetrachloride to 0.28 for m- and p-xylenes), while BCff and BCwb were highly variable (COD values of 0.46 and 0.50). The BCwb was well correlated with levoglucosan (R2 of 0.68 to 0.95), indicating that BCwb was a robust indicator for wood burning. At the two permanent monitoring sites, wood burning comprised 29–39% of the fine particulate matter (PM2.5) on nights when PM2.5 concentrations were forecasted to be high. Phone survey data were consistent with study measurements; the only significant difference in the survey results among communities were that non-EJ residents burn with indoor devices more often than EJ residents.


2012 ◽  
Vol 12 (8) ◽  
pp. 22535-22586 ◽  
Author(s):  
M. Crippa ◽  
P. F. DeCarlo ◽  
J. G. Slowik ◽  
C. Mohr ◽  
M. F. Heringa ◽  
...  

Abstract. The effect of a post-industrial megacity on local and regional air quality was assessed via a month-long field measurement campaign in the Paris metropolitan area during winter 2010. Here we present source apportionment results from three aerosol mass spectrometers and two aethalometers deployed at three measurement stations within the Paris region. Submicron aerosol composition is dominated by the organic fraction (30–36%) and nitrate (28–29%), with lower contributions from sulfate (14–16%), ammonium (12–14%) and black carbon (7–13%). Organic source apportionment was performed using positive matrix factorization, resulting in a set of organic factors corresponding both to primary emission sources and secondary production. The dominant primary sources are traffic (11–15% of organic mass), biomass burning (13–15 %) and cooking (11–17% and up to 35% during meal hours). Secondary organic aerosol contributes more than 50% to the total organic mass and includes a highly oxidized factor from indeterminate and/or diverse sources and a less oxidized factor related to wood burning emissions. Black carbon was apportioned to traffic and wood burning sources using a model based on wavelength-dependent light absorption of these two combustion sources. The time series of organic and black carbon factors from related sources were strongly correlated. The similarities in aerosol composition, total mass and temporal variation between the three sites suggest that particulate pollution in Paris is dominated by regional factors, and that the emissions from Paris itself have a relatively low impact on its surroundings.


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