Source apportionment of organic compounds in Berlin using positive matrix factorization — Assessing the impact of biogenic aerosol and biomass burning on urban particulate matter

Wagener, Sandra; Langner, Marcel; Hansen, Ute; Moriske, Heinz-Jörn; Endlicher, Wilfried

doi:10.1016/j.scitotenv.2012.07.039

Cited by 18 publications

(14 citation statements)

References 52 publications

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“…Significant negative correlations between temperature and biomass burning were already identified for the sampling sites of this study [14]. The expected [OC/EC] p -ratio of biomass burning emissions can…”

Section: Application With Regard To Temporal and Spatial Variationsupporting

confidence: 64%

“…Furthermore, some of the OC in PMF analysis was unapportioned, which can also be assumed to be in part secondary. Further details on the composition and the concentration of the factors are given in Wagener et al [14].…”

Section: Pmf-analysismentioning

confidence: 99%

“…The separation into both periods, which is almost identical with colder and warmer season, was also conducted for the HV and regV sites, so data evaluations for all sites were comparable. The determined [OC/EC] p -ratios for all sites and PM-fractions are given in Table 3 Note: POC bio is obtained from the sum of the 2 biogenic POA-factors bio primary and bio/urban primary in PM 10 and from the bio urban primary factor in PM 1 determined in source apportionment with PMF [14].…”

Section: [Oc/ec] P -Ratiomentioning

confidence: 99%

“…It has been applied in a number of studies based on the analysis of elemental constituents, OC and EC. Recently several studies estimating secondary organic carbon (SOC) by using PMF with organic compounds have been conducted [13][14][15]. Another technique is the EC-tracer method, which is based on the assumption of similar sources for anthropogenic primary organic carbon (POC) and EC [16,17].…”

Section: Introductionmentioning

confidence: 99%

“…OC and EC-PM 10 and PM 1 data were obtained from three measurement sites characterized by different vegetation influences in the city of Berlin from February to October 2010. The results of the EC-tracer method are assessed by comparing them to those determined by PMF-analysis in a previous study, which was based on the detection of single, mainly biogenic compounds determined for the same samples [14,22].…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Influence of Seasonal and Spatial Variations on the Estimation of Secondary Organic Carbon in Urban Particulate Matter by Applying the EC-Tracer Method

et al. 2014

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Abstract:The elemental carbon (EC)-tracer method was applied to PM 10 and PM 1 data of three sampling sites in the City of Berlin from February to October 2010. The sites were characterized by differing exposure to traffic and vegetation. The aim was to determine the secondary organic carbon (SOC) concentration and to describe the parameters influencing the application of the EC-tracer method. The evaluation was based on comparisons with results obtained from positive matrix factorization (PMF) applied to the same samples. To obtain site-and seasonal representative primary OC/EC-ratios ([OC/EC] p ), the EC-tracer method was performed separately for each station, and additionally discrete for samples with high and low contribution of biomass burning. Estimated SOC-concentrations for all stations were between 11% and 33% of total OC. SOC-concentrations obtained with PMF exceeded EC-tracer results more than 100% at the park in the period with low biomass OPEN ACCESSAtmosphere 2014, 5 253 burning emissions in PM 10 . The deviations were besides others attributed to the high ratio of biogenic to combustion emissions and to direct exposure to vegetation. The occurrences of biomass burning emissions in contrast lead to increased SOC-concentrations compared to PMF in PM 10 . The obtained results distinguish that the EC-tracer-method provides well comparable results with PMF if sites are strongly influenced by one characteristic primary combustion source, but was found to be adversely influenced by direct and relatively high biogenic emissions.

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Section: Application With Regard To Temporal and Spatial Variationsupporting

confidence: 64%

Section: Pmf-analysismentioning

confidence: 99%