Spatial and seasonal variations of biogenic tracer compounds in ambient PM10 and PM1 samples in Berlin, Germany

Atmospheric Environment 47 (2012) 33e42

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Spatial and seasonal variations of biogenic tracer compounds in ambient PM10 and PM1 samples in Berlin, Germany Sandra Wagener a, b, *, Marcel Langner a, Ute Hansen c, Heinz-Jörn Moriske b, Wilfried R. Endlicher a a

Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany German Federal Environmental Agency, Corrensplatz 1, 14195 Berlin, Germany c Biology Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 7 June 2011 Received in revised form 16 November 2011 Accepted 17 November 2011

PM10 and PM1 aerosol samples were collected between February and October, 2010 at three sites in Berlin that were characterized by different vegetation influences. The aim of the study was to determine the spatial and seasonal variations of several, mainly biogenic secondary and primary tracers in an urban area. Selected tracers including isoprene and a-pinene markers, fatty acids and levoglucosan were detected with GC-MS. The highest median concentrations, up to 45.1 ng m
3, were found for the combustion product levoglucosan. The concentration range of the secondary compounds was 0.3 ng m
3 for the isoprene markers 2-methyltetrols up to 35.7 ng m
3 for malic acid. The occurrence of these compounds was mainly affected by the seasons, which could be described by three patterns. Whereas secondary compounds were mainly characterized by significantly higher concentrations during the warmer months, levoglucosan showed significantly higher concentrations during the colder months. No significant concentration differences between the two periods were rather observed for the primary compounds but also for the a-pinene degradation product pinonic acid. The secondary compounds and levoglucosan could be associated with the fine mode (particles with an aerodynamic diameter (AD) < 1 mm), while primary compounds are rather associated with the coarse mode (AD > 1 mm). Spatial variations were emphasized with a tendency toward higher concentrations for most compounds at sites that were influenced by vegetation, especially evident for the PM10 fraction. Besides concentration differences, spatial variations could also be described by differences in seasonal behavior and the size distribution, indicating major complexity in the composition of biogenic PM within the city of Berlin. Ó 2011 Elsevier Ltd. All rights reserved.

Keywords: Biogenic aerosol Secondary organic aerosol Urban air quality Berlin

1. Introduction The organic fraction of atmospheric particulate matter (PM) has been investigated extensively in recent decades. While several studies have concentrated on organic matter of an anthropogenic origin, attention has increasingly been placed on biogenic organic compounds, especially particle constituents that are formed through secondary formation processes in the atmosphere (Hoffmann et al., 1997; Claeys et al., 2004; Kourtchev et al., 2008a) Previous studies have already highlighted biogenic influences on a global scale. Biogenic volatile organic compound (VOC) emissions were estimated to be 10 times higher than those of anthropogenic VOCs

* Corresponding author. Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany. Tel.: þ49 30 89031843; fax: þ49 30 20936844. E-mail address: [email protected] (S. Wagener). 1352-2310/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2011.11.044

(Guenther et al., 1995). Tsigaridis and Kanakidou (2003) extended a model in which they determined an annual biogenic secondary organic aerosol (SOA) production between 2.5 and 44.0 TG y
1, whereas the production due to anthropogenic precursors varied from 0.05 to 2.62 TG y
1. Although the impact of vegetation is lower in urban areas, and anthropogenic sources dominate total VOC emissions, biogenic influences on urban areas should not be ignored; e.g. Szidat et al. (2004) found that 51e80% of the organic carbon in an urban background site in Zürich, Switzerland was of biogenic, mainly secondary origin, concluding that the carbonaceous aerosol at this site mainly originates from the nearby rural area. The contribution of biogenic aerosols in urban areas is also of interest in the context of strategies that were developed to reduce the particle concentrations in urban air. On the one hand vegetation can enhance dry deposition due to the enlarged particle deposition surface provided by leaves (Langner et al., 2011). Even though a single tree has limited filter efficiency, a major vegetation inventory may lead to a significant reduction in particle concentrations.

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S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

Furthermore, a dense vegetation cover acts as an obstacle to air flow, preventing the dispersion of particles at locations with increased particle emissions, such as street canyons (Gromke and Ruck, 2009). Attempts to evaluate the potential role of vegetation as an additional particle sink within urban areas require the assessment of both, its potential as a particle sink and the contribution of vegetation emissions to particle concentrations. Estimations of the contribution of total biogenic organic carbon to ambient OC concentrations have been conducted using radiocarbon analysis (Szidat et al., 2004) or aerosol mass spectrometer (AMS) measurements (Zhang et al., 1999). To obtain information about individual sources, single compound analysis is necessary. In urban regions, the main focus has been on determining single compounds from mainly anthropogenic sources (Alves et al., 1999; Bi et al., 2008). Previous studies concerning single biogenic compounds, which have focused on SOA, were conducted mainly over boreal forests (Kourtchev et al., 2008a) or under simulated laboratory conditions (Presto et al., 2005). Recently, several studies have been conducted on the occurrence of secondary biogenic organic tracers within urban areas. For example Ding et al. (2008), Lewandowski et al. (2008) and Stone et al. (2009) reported spatial and seasonal variations between cities or regions in the US and the dependence of local emissions on particle concentrations, highlighting the complexity and special circumstances that lead to different contributions at different locations. This study is part of a project that aims to investigate the contribution of biogenic aerosol constituents to ambient PM10 and PM1 concentrations within areas that are under different vegetation influences. The focus of this study is quantifying several primary and secondary, mainly biogenic tracers in aerosol samples that were collected over a period of nine months in Berlin using gas chromatography-mass spectrometry (GC-MS). The resulting data were used to assess spatial and seasonal variability and to yield insight to the urban and regional vegetation. 2. Experimental 2.1. Sampling site Aerosol samples were collected at three different measurement sites in Berlin, Germany. Berlin is situated in the North-East of Germany in the temporate zone with main wind directions from north-west and south-west. It is surrounded by the state of Brandenburg, which exhibits a forest area of about 1,000,000 ha with mainly pines and some minor stocks of oaks and beeches. The forests of Berlin are 29,000 ha in size with mainly pines. Deciduous types are oaks, birches and beeches. The growing season in 2010 started at the end of April. Until the end of October, the fall of the leaves was not completed yet. The first sampling site was in the “Großer Tiergarten,” a large, 210-ha urban park in the center of Berlin (Fig. 1) that predominantly contains maples, oaks and beeches; this site is referred to as a site with high vegetation stock (HV). The setup was positioned approximately 100 m away from the nearest road, in between were narrow tree populations. The traffic density there was about 35,000 vehicles per working day (Senatsverwaltung für Stadtentwicklung Berlin, 2005). The second sampling site, in the west of the city, was a traffic station in the immediate vicinity of the A 100 Berlin urban motorway with low vegetation stock (LV). The motorway carries more than 100,000 vehicles per working day. A residential area with dense, multistory buildings was adjacent to the north. The equipment was placed on top of a container at an altitude of about three meter to the road. The third location was in Adlershof in the southeast of Berlin. The setup was established on top of the Geographic Department of the Humboldt-Universität zu Berlin, which is part of the Technology

Fig. 1. Location of the sampling sites

Center Adlershof, at an altitude of approximately 20 m. Due to the altitude and the location toward the outskirts, as well as the interest to biogenic compounds, this site was suited for a background station and is referred to as a site with a regional influence of vegetation (regV). 2.2. Sample collection Sampling took place each 6th day from February 2010 to October 2010 at all measurement sites. For the analysis, atmospheric particles were collected on glass fiber filters (Pallflex, Tissuquartz 2500QAT-UP, 47 mm) using low-volume samplers (LVS3.1, Derenda) at a flow rate of 2.3 m3 h
1. The aerosol inlet was 2 m above the ground. The collection time was 24 h. In parallel to the aerosol sampling for analysis, additional PM10 samples were taken for 24 h at the urban motorway and for 144 h in Adlershof for gravimetric determinations. Temperature, relative humidity and wind velocity were measured using a Davis weather Monitor IIÒ. Additional PM10 concentrations at several urban measurement sites were provided by the “BLUME” meteorological network of Berlin, which is operated by the Senate Department for Health, Environment and Consumer Protection. 2.3. Laboratory measurements Before sampling, filters were preheated at 700  C for 8 h to remove organic impurities. After sampling, the loaded filters were stored until analysis in airproofed petri dishes covered with aluminum foil at
18  C. To obtain information about the sources and transport of biogenic PM in urban areas, biogenic compounds that are assumed to be meaningful tracers and have already been found in the urban aerosol were pre-selected (Table 1). On the basis of the methods of Pashynska et al. (2002) and Kourtchev et al. (2008a), an analytical procedure and a GC-MS method were enhanced, allowing the detection of all compounds of interest. One half of the quartz fiber filter was spiked with internal recovery standards (IS) (Table 1) to correct for procedural and instrumental variability. The spiked filters were left to dry for approximately 15 min and were then extracted four times with 8 ml of a methanol:dichloromethane solution (20:80) in an ultrasonic bath for 15 min each time. The combined suspensions were filtered through a Teflon filter. The filtrate was then transferred to a test tube and evaporated to dryness under a nitrogen stream. The residue was derivatized by adding 10 ml of N-methyl-N-trimethylsilyltrifluoroacetamide containing 1% trimethylchlorosilane (MSTFA þ 1% TMCS) and 10 mL pyridine and kept at 70  C for 1 h. After cooling to room temperature, a 1-mL aliquot was analyzed by GC-MS. An extraction

S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42 Table 1 Selected compounds for analysis, their corresponding internal standards (IS) and base ion fragments. Internal Standard

Analyte

Base ion fragments

Malic acid Adipic acid Pinonic acid Pinic acid 2-Methyltetrols

108, 329 233 275 98 157, 315 189, 277

Levoglucosan Glucose

204, 217 333 204, 217

C14 C15 C16 C18:1 C18

135, 344 285 299 313 339 341

Camphoric acid

meso-Erythritol MXP (methyl-b-D-xylanopyranoside)

Palmitic acid-d31

efficiency of approximately 80% could be achieved with little variation between compounds, determined by comparing each single standard in a given concentration with and without adding it to the filter. The GC-MS equipment consisted of an Agilent gas chromatograph with a fused silica capillary column (Rtx-5MS; 30 m  0.25 mm i.d., 0.25 mm film thickness), a quadrupole mass spectrometer from Hewlett Packard, a cold injection system (CIS) and an autosampler from Gerstel. The temperature program of the column was initial temperature 50  C (hold for 5 min), then 3  C/min up to 200  C (hold for 4 min), followed by 6  C/min up to 300  C (hold for 5 min). Compound identification was achieved by comparing the results to the mass spectra and retention times of authentic standards. The 2-methyltetrols, for which no authentic standards were available, were compared to reported mass spectra and retention times (Kourtchev et al., 2005). For qualitative and quantitative analyses, the selected ion monitoring (SIM) mode was used. Selected base ion fragments are listed in Table 1. For all authentic standards, calibrations of five different concentrations were performed in the SIM mode. The IS were applied at the same concentration for all calibrations and samples. Taking the relationship of the abundance of each standard to its IS, the concentration of each compound was calculated. The quantification of the 2-methyltetrols was solely based on the use of an IS, namely meso-erythritol, as the responses of the derivatives of this standard and the analytes are expected to be similar due to their structural similarity (Kourtchev et al., 2005). Therefore, the mass fragments 189 and 277 were chosen, which are meaningful fragments that occur in both the standard and the 2-methyltetrols (Wang et al., 2004). Each derivatized sample was analyzed twice with GC-MS. The deviation was generally 10% or less. Values with increased uncertainties were excluded for further analyses. As most blank values did not produce signals outside the noise of the instrument, the limit of detection was calculated from the mean þ 3 S.D. of those concentration levels of each compound corresponding to a S/ N-ratio w 5. From that, the effective limits of detection (further on termed as LOD) were calculated, resulting in 0.5 ng m
3 for pinonic acid and malic acid and 0.1 ng m
3 for the remaining compounds which were required on the filter to be detected at the corresponding extraction efficiency. Occurring blank values above LOD were subtracted from the measured sample concentrations. During first analyses, which included most of the PM10 samples, malic acid produced unstable duplicate measurements, which is why only PM1 data are presented here. The fatty acids in PM10 exhibit a data gap from February to June. During analyses of those

35

samples, the IS used was gradually proved as less suitable and was replaced. In this sudy, the fatty acids C14 to C18:1 are presented (termed after their chain length, i.e. number of C-Atoms), except of C17, which overlapped in retention time with other compounds and needed to be excluded for further analyses. 3. Results and discussion 3.1. Concentrations 3.1.1. SOA compounds a-pinene-oxidation products. Pinic and pinonic acid are the major oxidation products of a-pinene (Presto et al., 2005), the most abundant monoterperne (Guenther et al., 1995). The observed concentrations (Table 2) ranged from below LOD (BLOD) to 35 ng m
3 for pinic acid and from BLOD to 132 ng m
3 for pinonic acid, with the highest median and maximum concentrations at site regV for both compounds. Thus, the strongest influence seems to originate from the regional background. This is consistent with the domination of pines, which emit larger amounts of a-pinene, in these areas compared to site HV, where these types rarely occur. Similar annual mean concentrations for pinonic acid at three different urban locations in the southern US were found by Ding et al. (2008). Lower mean concentrations in German urban areas were found in Mainz, with 1.51 ng m
3 for pinic acid and 0.6 ng m
3 for pinonic acid in annual PM3 samples (Zhang et al., 2010). 2-methyltetrols are formed by photo-oxidation processes of isoprene (Claeys et al., 2004) and have been used as tracers for isoprene emission (Kourtchev et al., 2005; Xia and Hopke, 2006; Stone et al., 2009). Deciduous trees are assumed to be responsible for a major amount of isoprene emissions, which accords with their first occurrence in May, when the leaves of deciduous trees just started to develop. The concentrations ranged from BLOD to 6.3 ng m
3 for 2-methylthreitol and BLOD to 6.7 ng m
3 for 2-methylerythritol. Highest median concentrations were found at site HV, indicating a strong influence of urban trees, which is consistent with the domination of deciduous trees at that site compared to the regional background. According to results of previous studies, 2-methylerythritol was present at higher concentrations than 2-methylthreitol. They mostly occurred together and showed similar time series, as reported before by Claeys et al. (2010). Higher concentrations for the 2-methyltetrols in urban regions were observed in several US-cities. Stone et al. (2009) reported concentrations of 3.3e46.2 ng m
3 in PM2.5 summer samples at two sites in the Midwestern-US. Xia and Hopke (2006) found concentrations up to 54 ng m
3 and 77 ng m
3, respectively for PM2.5 samples during the months June to December in Potsdam, New York. Concentrations between 1.4e16.1 ng m
3 for both compounds were reported for PM2.5 summer samples taken at a mixed forest site in Germany (Kourtchev et al., 2008b). The reasons for this high variability can result from differences in vegetation stock, light intensity and temperature affecting the emission rates of isoprene, and/or isoprene degradation, which leads to higher yields of photo-oxidation products. Furthermore, 2-methyltetrol concentrations in PM are assumed to be affected by the acidity of the aerosol due to higher concentrations of HNO3 and SO2 (Lewandowski et al., 2007; Kourtchev et al., 2008a) and the occurrence of NOX, which plays an important role during formation processes (Claeys et al., 2010). However, whether the respective variables affected the concentrations reported here cannot be determined at this point. Malic acid is assumed to be an oxidation product of dicarboxylic acids. Dicarboxylic acids are formed through the photo-oxidation of semivolatile unsaturated fatty acids (Kawamura and Ikushima, 1993) which in turn can be of multiple origin. Reported biogenic sources are plant waxes, fungi or pollen (Simoneit and Mazurek, 1982)

36

S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

Table 2 Median, mean, minimum and maximum values for tracers in ng m
3 at all measurement sites since first appearance (Fa). PM10

Pinic acid Pinonic acid 2-Methylthreitol 2-Methylerythritol Malic acid Adipic acid Levoglucosan Glucose C14a C15a C16a C18:1a C18a PM (mg m
3) PM1

Pinic acid Pinonic acid 2-Methylthreitol 2-Methylerythritol Malic acid Adipic acid Levoglucosan Glucose C14 C15 C16 C18:1 C18

HV

LV Max

Nd

Med

Mean

2.9 7.6 0.6 1.0 e 1.6 42.4 10.1 6.1 2.4 5.3 7.4 2.9 20.0c

3.9 13.2 0.8 1.4

13.8 73.9 2.8 4.3

34 35 23 23

(38) (38) (38) (38)

2.0 63.5 15.3 5.9 2.3 7.8 8.4 7.1 21.4

6.3 275.0 64.4 9.2 5.4 28.9 29.5 40.9 103.0

34 38 35 17 13 17 13 14 44

(38) (38) (38) (17) (17) (17) (17) (17) (44)

regV

Med

Mean

1.5 5.4 0.4 0.7 e 0.9 45.1 10.0 4.7 1.8 5.7 3.2 4.7 22.3

2.2 8.4 0.6 1.2

10.0 61.6 2.5 6.1

29 38 25 24

(39) (40) (42) (42)

1.5 56.6 14.9 5.2 1.9 7.5 5.8 5.9 26.2

7.3 275.0 64.3 12.5 6.0 30.9 24.1 22.8 103.0

31 44 42 17 13 16 15 14 44

(38) (44) (44) (19) (19) (19) (19) (19) (44)

HV

Max

N

Med

Mean

Max

N

3.7 9.0 0.3 0.3 e 1.6 41.5 9.1 4.7 1.5 5.4 7.5 2.9 16.3

5.6 15.3 0.8 1.2

35.0 132.0 6.3 5.7

31 38 23 23

(39) (41) (41) (41)

12.4 75.6 15.1 5.9 2.6 8.6 8.4 5.9 19.5

12.9 425.0 52.5 18.8 5.9 27.6g 23.0 26.2 97.7

31 43 40 18 14 19 15 16 44

(38) (43) (42) (19) (19) (19) (19) (19) (44)

LV

Med

Mean

Max

N

2.2 8.0 0.3 0.5 35.7 1.8 18.4 0.5 3.3b 1.7b 0.9b 1.9b 0.1b

3.1 11.9 0.6 1.1 66.1 2.1 40.2 1.1 3.7 1.8 1.3 2.6 1.1

11.7 67.3 3.4 6.7 356.0 8.9 239.5 6.1 9.6 5.4 5.6 9.4 5.6

38 38 22 24 36 38 41 35 36 33 27 29 19

(39) (39) (39) (40) (38) (40) (41) (41) (38) (38) (38) (38) (38)

Fa

Med

Mean

Max

N

1.3 3.1 0.2 0.5 16.5 0.6 25.1 0.7 4.8 2.8 1.6 1.8 0.4

2.3 6.9 0.3 0.8 34.0 1.3 38.4 1.1 5.0 2.6 2.0 2.4 0.9

14.0 24.0 3.1 5.7 182.0 8.1 223.6 7.7 16.8 5.9 7.5 15.9 7.6

39 36 23 25 40 35 43 27 38 33 32 30 27

(41) (40) (42) (42) (43) (42) (43) (42) (40) (40) (40) (40) (40)

Feb Feb May May Feb Mar Feb Feb Feb Feb Feb Feb Feb

HV ¼ measurement site with high vegetation stock; LV ¼ measurement site with low vegetation stock; regV ¼ measurement site with regional influence of vegetation. Since minimum values were BLOD in most cases, only maximum values instead of the concentration range is indicated; exceptions are given by eminimum value ¼ 3 ng m
3; f minimum value ¼ 2 ng m
3; gminimum value ¼ 1 ng m
3; hminimum value ¼ 9.1 mg m
3; iminimum value ¼ 7.3 mg m
3; iminimum value ¼ 7.5 mg m
3. a Detected for the month July to October. b Detected for the month March to October. c Values provided by BLUME for a similar station close to HV. d Number of samples above LOD (number of all analyzed samples).

anthropogenic compounds derive from cooking emissions (Rogge et al., 1991). Previous studies attributed malic acid to be primarily formed from biogenic precursors (Röhrl and Lammel, 2002; Kourtchev et al., 2005). Other possible sources of malic acid were proposed by Claeys et al. (2004), suggesting biogenic VOCs other than unsaturated fatty acids as possible precursors. In this study, malic acid was one of the most abundant compounds. It showed the highest spatial variability, with a concentration of 35.7 ng m
3 at site HV and 16.5 ng m
3 at site LV, pointing to a major contribution of biogenic sources at site HV. The concentration levels agree with results obtained by Kourtchev et al. (2008b), who reported median summer concentrations of 37 ng m
3 at a mixed forest site in Germany for the PM2.5 fraction. The annual mean value for aerosol samples detected in urban areas in Leipzig and close to Berlin, Germany, was 54 ng m
3 (Röhrl and Lammel, 2002). Adipic acid can be of secondary and primary origin. Reported sources are the ozonolysis of anthropogenic cyclohexene (Hatakeyama et al., 1987) and meat cooking emissions (Rogge et al., 1991). The first appearance was in March. The median concentrations are below 1.8 ng m
3; with lowest concentrations found at site LV, the maximum concentration occurred at site regV. Similar low annual mean values of 0.78 ng m
3 in PM3 were found in an urban area in Mainz, Germany (Zhang et al., 2010). Clearly higher median concentrations of PM2.5 summer and winter samples, however, were found in Hong Kong, China (3.78e32.1 ng m
3) (Ho et al., 2006) and several other Chinese cities (up to 23.5 ng m
3), as reported by Ho et al. (2007) (in Zhang et al., 2010).

Concentration differences between the sites show a tendency toward higher concentrations at site HV and regV. In comparison with Table 3, the temperature and the humidity show similar values between the sites. Thus, these parameters do not seem to effect substantially the observed concentration differences. They more likely result from differences in emission source and strengths for each site, but there is also a hint that higher wind velocities may influence increased or decreased concentrations. Fig. 2a shows the time series of both fractions at all sites. As can be seen, in a few samples PM1 concentrations exceed PM10 concentrations. In some cases these are within the range of measurement uncertainty. However, some scattered values show clear higher values for the PM1 fraction. These apply above all to one sample in may for the 2-methyltetrols and two samples for pinic acid at site LV, for latter the PM10 values can be expected to be too low in comparison with the other sites. Reasons for these differences can only be assumed and might be due to variances between the air masses or effects during sampling. Both fractions of the secondary compounds are within a similar concentration range, furthermore, the time series partly follow each other (this also refers to adipic acid, which is not presented in the figure). Thus it can be concluded that all secondary compounds are rather associated with the fine mode, which is consistent with their origin of secondary formation. Kourtchev et al. (2009) determined an exclusive association of pinic acid to the fine mode. In the case of the 2-methyltetrols, they detected these compounds in both modes, what agrees with the results presented here, at least for site

S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

37

Table 3 Mean, minimum and maximum values for temperature, relative humidity and wind velocity for cold months (February to April, September and October) and warm months (May to August). Temperature ( C)

Site

Wind velocity (m s
1)

Relative humidity (%)

Mean

Min.

Max.

Mean

Min.

Max.

Mean

Min.

Max.

HV

Cold months Warm months

7.7 16.8


2.9 9.0

14.7 29.4

74.8 73.7

45.6 54.4

95.9 96.0

0.2 0.4

0.0 0.0

0.5 2.6

LV

Cold months Warm months

8.3 17.5


2.7 9.9

15.9 31.0

73.5 69.6

41.4 47.1

93.1 96.0

1.2 0.9

0.2 0.1

2.5 1.7

regV

Cold months Warm months

7.8 17.1


3.2 9.5

15.3 31.0

76.0 72.5

47.7 47.1

94.8 96.0

1.5 1.4

0.2 0.1

2.8 2.6

LV. Lower PM1/PM10 ratios at site LV compared to site HV were also observed for pinonic acid and adipic acid. These observations indicate advanced particle growth at site LV. 3.1.2. Primary compounds Levoglucosan is a cellulose combustion product and is used as a significant tracer for biomass burning. The median concentrations were 41.5, 42.4 and 45.1 ng m
3 for PM10 for sites regV, HV and LV, respectively. The variations among sites were low, which can be explained by the high stability of levoglucosan (Fraser and Lakshmanan, 2000). However, a slight tendency toward higher levels can be observed at site LV, especially in the PM1 fraction, which is characterized by a stronger anthropogenic influence on air. The maximum concentration however occurred at site regV. Jordan et al. (2006) found distinctly higher concentrations between 1.4 and 16 mg m
3 in Launceston, Australia for winter samples and up to 0.47 mg m
3 for summer samples. Fraser and Lakshmanan (2000) reported 0.2e1.2 mg m
3 for different cities in Texas in the US in May. Concentrations approximate to those presented here were reported by Puxbaum et al. (2007), who found concentrations from 2.3 to 66.3 ng m
3 in the summer and from 6.6 to 1290 ng m
3 in the winter for low- and high-level background sites in Europe. The lower concentrations found in this study show that heating systems that are based on wood burning are less common in Berlin and the surrounding area than in urban areas in Australia or Texas. Nevertheless, levoglucosan had the highest concentration of all detected compounds, suggesting wood burning as a major source for particulate matter in Berlin. Glucose mainly originates from vascular plants; plant pollen, spores and other plant fragments are major sources (Graham et al., 2003). The concentrations ranged between BLOD to 64.4 ng m
3 and were similar between the stations. Similar concentrations of 15 ng m
3 were reported by Kourtchev et al. (2008b) for PM2.5 summer samples of a mixed forest in Germany. Higher concentrations for urban background samples in Oslo, Norway were reported by Yttri et al. (2007), who determined concentrations of 47 ng m
3 for PM10 and 7.2 ng m
3 for PM2.5 aerosol in the fall. Fatty acids are of anthropogenic and biogenic origin. The latter include microbial activity, lipids from microflora or waxes of vascular plants. Anthropogenic sources include fossil fuel combustion, wood combustion and meat cooking (Simoneit and Mazurek, 1982; Simoneit, 1985; Rogge et al., 1991). C14 and C18:1 showed highest median concentrations, with up to 6.1 and 7.5 ng m
3, respectively, and C15 the lowest (up to 2.8 ng m
3). However, the maximum concentrations were highest for C18, C16 and C18:1, at 40.9, 30.9 and 29.5 ng m
3, respectively. Previous studies (Cheng et al., 2004; Kourtchev et al., 2008b) showed higher median concentrations for C16 in PM2.5 urban summer samples, with 20 ng m
3 in the Greater Vancouver area and 21 ng m
3 at a mixed forest site in Germany. C18 concentrations of 8.7 ng m
3 were reported at the German site. For C18:1 Kourtchev et al. (2008b) found a median concentration of

3.5 ng m
3, whereas Rogge et al. (1993) reported concentrations of 6 ng m
3 during the summer and nearly 80 ng m
3 during the winter. The clear dominance of C16, as reported by Kourtchev et al. (2008b) and Cheng et al. (2004), was not observed in this study, even though the maximum concentrations reached similar values. The median concentrations for C14 and C15 were in agreement with their findings. They show highest concentrations at site HV in PM10 samples but lower concentration in PM1 samples. C16 and C18 show higher concentrations at site LV in PM1 samples, and C18 also in PM10 samples. The size distribution for the primary compounds shows different pattern. For levoglucosan, C14 and C15, more than 50% of their mean concentrations are in the PM1 fraction (compare Table 2). As can be seen in Fig. 2b, the time series of levoglucosan of both fractions follow each other as already observed for the secondary compounds, associating it also with the fine mode. Similar findings for levoglucosan were reported by Claeys et al. (2010), who explained it as the condensation of low-volatile organic vapors emitted during high-temperature wood combustion processes. In contrast, glucose shows clearly lower concentration ranges in the PM1 fraction and is attributed to the coarse mode, indicating primary biogenic sources. This agrees with previous findings from Graham et al. (2003), who attributed glucose primarily to biogenic sources like pollen or spores. However, during the first months the concentration differences between both fractions tend to be lower. Yttri et al. (2007) also found higher PM1 ratios in winter samples, attributing it to biomass burning. Prevalence in the coarse mode is also found for the higher fatty acids. The dominance of fatty acids in that mode is also often associated with biogenic sources (Graham et al., 2003). This is additionally supported by higher concentrations of some fatty acids in PM10 at site HV. This also includes C14 and C15, which, despite of higher PM1/PM10 ratios, still show higher concentrations in PM10. Cooking emissions can also be assumed to contribute little to that site, since near this area, people sometimes have barbecues (however, barbecuing was prohibited during the months June and July). As most fatty acids show higher PM1 concentrations at site LV, a stronger contribution of anthropogenic sources, assumedly fossil combustion can be assumed for this fraction. 3.2. Time series To characterize the seasonal variation of all compounds (except of the PM10 fraction of the fatty acids), PM (PM10) and the meteorological parameters from Table 3, the sampling period was distinguished between colder months (February to April, September and October) and warmer months (May to August). To point out potential differences between the two periods, the ManneWhitney U-test was performed at a significance level of 0.05. Three characteristic patterns of seasonal variation could be observed, comprising significantly higher concentrations during the warmer months, significantly lower concentrations during the warmer months and concentrations with no significant differences between these

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S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

Fig. 2. a: Time series of secondary compounds and temperature. b: Time series of primary compounds and PM (PM10). Concentrations are in ng m
3, except for PM (mg m
3). Occurring data gaps result from increased measurement uncertainties for these values. Exceptions are given in PM10 at site HV by two samples each, in June and October, where sampling had to be interrupted. 1: Significantly higher concentrations during warmer months; 2: No significant concentrations differences between warmer and colder months; 3: Significantly higher concentrations during colder months; 4: Exception is given by PM10 at site LV with no significant concentration differences; 5: Exception is given by PM1 at site LV with higher concentrations during warmer months, 6: Temperature is given at the example of site regV; 7: No significant concentration differences at site HV, significantly higher concentrations during warmer months at site LV.

S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

39

Fig. 2. (continued).

periods. Compounds with higher concentrations during the warmer months are most secondary oxidation products (including adipic acid) and all fatty acids measured at site LV (Fig. 2a and b). It can be seen that, after the first occurrence of each compound of that group, the time series are similar to the time serie of the air temperature. In the cases of the 2-Methyltetrols and pinic acid, this typical variation pattern can be explained by the higher light intensity and

temperature, which leads to higher emission rates of isoprene and apinene and higher reaction rates (Rinne et al., 2002; Ion et al., 2005), and is in agreement with findings from other studies (Ding et al., 2008; Yan et al., 2009; Zhang et al., 2010). The 2-methyltetrols appeared later than the a-pinene oxidation products, which can be explained by different sources for isoprene and terpene emissions and therefore by different vegetation periods, leading to a slower

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S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

decrease of terpene emissions during the colder months (Lamb et al., 1987; Yan et al., 2009). For most time series of pinonic acid, no obvious seasonal variation was observed, in contrast to pinic acid, due to the higher concentrations occurring in March, September and October. However, taking the first measurements of February as an indicator for concentrations BLOD in the winter, a clearer seasonal variation would likely be seen if the time series had included an entire year. Nevertheless, Ding et al. (2008), who analyzed data for pinonic acid only, neither observed seasonal variation. They observed a weakly negative correlation with temperature; this correlation, however, was not observed in the present study. As these observations apply to all sites, they might indicate different meteorological conditions that lead to the formation of pinonic and pinic acid. These assumptions are strengthened by the findings of Zhang et al. (2010), who determined a decreased temperature dependence of pinonic acid concentrations compared to pinic acid and pinene emissions. However, Yan et al. (2009) reported even higher concentrations for both, pinic and pinonic acid in winter samples in Atlanta. These differences in seasonal behavior at different locations can be explained by different existing tree types, which emit different amounts of monoterpenes throughout the year. In summary, it can be assumed that the aerosol yields of pinic acid and pinonic acid depend on the vegetation structure as well as on meteorological conditions and might differ between these two species and different locations. The affinity between the time series of temperature and malic acid, which is especially evident at site HV, points to biogenic emissions as major sources, which are emitted more strongly during warmer months and accords with the findings and conclusions of Röhrl and Lammel (2002) and Kourtchev et al. (2005) and the previous discussion concerning spatial concentration variations. However, malic acid shows higher concentrations during the colder months compared to the other oxidation products, indicating the possibility of anthropogenic sources, probably cooking emissions, during these months, which are emitted throughout the year in urban areas. Studies from China and Tokyo reported similar mean concentrations of adipic acid in summer and winter samples (Kawamura and Yasui, 2005; Ho et al., 2006). The higher summer concentrations found in the present study and the lower concentrations, as discussed previously, indicate that relevant sources and effects of atmospheric processes differ between different locations. Levoglucosan is the only compound showing higher concentrations during the colder months. The time series show a clear opposite seasonal variation and a consistent turning point with respect to temperature, which can be explained by the decreased heating during warmer months. Other possible reasons for the higher concentrations during these months may be reduced atmospheric dispersion in the winter (Yan et al., 2009) The third group applies, besides pinonic acid, to glucose, all fatty acids measured at site HV and PM. Glucose however shows a tendency of increasing concentrations from February to October for the PM10 fraction, with similar trends at all stations, indicating a concentration peak during the autumn season. These observations are in agreement with the findings from Yttri et al. (2007), who explained it with emissions of fungal spores that dominate during the autumn at that measurement sites in Norway and which were attributed to the coarse mode. Pashynska et al. (2002) found higher concentrations of 270 ng m
3 in the summer and 73 ng m
3 in the winter, suggesting developing leaves as source. For most secondary products, levoglucosan and glucose, all sites show the same seasonal pattern for each compound, pointing to a more regional influence. In the case of the PM10 fraction of pinic acid at site LV (Fig. 2a) differences might result from the missing values in May. Following the other time series, higher

concentrations at these days can also be suggested which then might lead to significantly higher concentrations during the warmer months. The significantly higher concentrations for pinonic acid in PM1 at site LV result from the lower concentrations in March and April compared to site HV. Following the assumption of advanced particle growth already discussed for the size distribution at site LV, the different time series in PM1 seem to result from varying formation processes rather than from emission patterns differing in seasonal behavior at the different sites. For the PM1 fraction of the fatty acids, no clear seasonal variation that is characteristic for one species could be determined. However, there seem to be apparent differences between the sites LV and HV (given by the examples of C14 and C16). For all five fatty acids, higher concentrations in summer can be observed at site LV. At site HV, a seasonal variation was not observed for any compound, Furthermore, many values are near or below LOD, indicating an additional or stronger influence of anthropogenic sources on fatty acids at site LV, as already discussed for spatial concentration differences. However, at this point it is not clear why anthropogenic emissions would result in increasing concentrations during the warmer months and remains to be examined. Higher concentrations in the winter than in the summer for PM2.5 samples were described by Oliveira et al. (2007) in two Northern and Southern European cities. No characteristic variations between summer and winter seasons could be determined by Ho et al. (2007) for four sampling sites in China, except for C14, which showed higher concentrations in the summer at all four sites. In comparison with PM, it can be seen that no compound follows the time series, thus the concentrations do not seem to be majorly affected by the variances in PM concentrations. As the parameter wind velocity and relative humidity do not show significant differences in time series between the two periods, it can be assumed that the temperature is the determinant factor for seasonal variations for most secondary compounds and levoglucosan. The other primary compounds as well as pinonic acid seem to be more or additionally influenced by other parameters like different emissions sources and strengths or formation processes that are influenced by other meteorological conditions and will be examined in more detail in further studies.

4. Summary and conclusions PM10 and PM1 concentrations for several biogenic markers were determined over a period of nine months at three different locations in the city of Berlin. The PM10 concentrations of the compounds tended to be higher at site HV and regV, with most maximum values observed at site regV. In PM1 higher concentrations at site HV occurred for the secondary compounds. The occurrence of the compounds was strongly affected by seasons, and could be characterized by three patterns of seasonal variation with significantly higher or lower concentrations, respectively, during warmer months, and no significant concentration differences between both periods. Remarkable was that pinonic acid, as the only compound of the secondary products, did not significantly increase in concentration during the warmer months, and was therefore assumed to be less dependent on temperature than pinic acid. Spatial differences in the time series were found for the PM1 fraction of the fatty acids, where only site LV showed significantly higher concentrations during the warmer months. Spatial variations in the size distribution suggesting particle growth at site LV for pinonic and adipic acid. Besides spatial and seasonal variations, the observation of levoglucosan showing the highest concentrations should be kept in mind when discussing limit values of PM-concentrations and biomass burning as renewable energy.

S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

This study provides a comprehensive overview of the occurrence of biogenic compounds within an urban area. In summary, Berlin, which can be seen as a green metropolis within the temperate latitudes, shows patterns of occurrence that are predominantly affected by the season; however, spatial variations could also be observed. These could not only be specified by concentration differences, but also by seasonal behavior and the size distribution. Further investigations focusing on meteorological conditions will be required to increase our knowledge about the sources, atmospheric processes and transportation of aerosol that lead to the observed variations. Future studies in source apportionment by performing Positive Matrix Factorization (PMF) and wind trajectories are planned. Furthermore, the use of EC/OC data as well as radiocarbon analysis are intended to obtain more information about secondary formation processes and the contribution of total biogenic aerosols.

Acknowledgements This work was supported by the Deutsche Forschungsgesellschaft (DFG). The authors would like to thank the “Parks and Gardens Department of Berlin, Mitte”, who allowed placing measurement equipment on their premises. The colleagues of the German Federal Environmental Agency, especially Klaus-Reinhard Brenske, are acknowledged for their technical support during measurements and analysis. We are grateful to the working group of Prof. Hoffmann at the Institute for Inorganic Chemistry and Analytical Chemistry of the Johannes Gutenberg-University, Mainz, especially to Anna van Eijck, and to the working group of Prof. Zimmermann at the Institute of Ecological Chemistry at the Helmholtz Zentrum München, who supported this work with methodical and analytical suggestions and further discussions.

References Alves, C., Pio, C., Duarte, A., 1999. The organic composition of air particulate matter from rural and urban portuguese areas. Physics and Chemistry of the Earth 24, 705e709. Bi, X., Simoneit, B.R.T., Sheng, G., Ma, S., Fu, J., 2008. Composition and major sources of organic compounds in urban aerosols. Atmospheric Research 88, 256e265. Cheng, Y., Li, S.M., Leithead, A., Brickel, P.C., Leaitch, R.W., 2004. Characterizations of cis-pinonic acid and n-fatty acids on fine aerosols in the Lower Fraser Valley during Pacific 2001 Air Quality Study. Atmospheric Environment 38, 5789e5800. Claeys, M., Graham, B., Vas, G., Wang, W., Vermeylen, R., Pashynska, V., Cafmeyer, J., Guyon, P., Andreae, M.O., Artaxo, P., Maenhaut, W., 2004. Formation of secondary organic aerosols through photooxidation of isoprene. Science 303, 1173e1176. Claeys, M., Kourtchev, I., Pashynska, V., Vas, G., Vermeylen, R., Wang, W., Cafmeyer, J., Chi, X., Artaxo, P., Andreae, M.O., Maenhaut, W., 2010. Polar organic marker compounds in atmospheric aerosols during the LBA-SMOCC 2002 biomass burning experiment in Rondônia, Brazil: sources and source processes, time series, diel variations and size distributions. Atmospheric Chemistry and Physics 10, 9319e9331. Ding, X., Zheng, M., Yu, L., Zhang, X., Weber, R.J., Yan, B., Russell, A.G., Edgerton, E.S., Wang, X., 2008. Spatial and seasonal trends in biogenic secondary organic aerosol tracers and water-soluble organic carbon in the southeastern United States. Environmental Science and Technology 42, 5171e5176. Fraser, M.P., Lakshmanan, K., 2000. Using levoglucosan as a molecular marker for the long-range transport of biomass combustion aerosols. Environmental Science and Technology 34, 4560e4564. Graham, B., Guyon, P., Taylor, P.E., Artaxo, P., Maenhaut, W., Glovsky, M.M., Flagan, R.C., Andreae, M.O., 2003. Organic compounds present in the natural Amazonian aerosol: characterization by gas chromatography-mass spectrometry. Journal of Geophysical Research 108 (D24), 4766. Gromke, C., Ruck, B., 2009. On the impact of trees on dispersion processes of traffic emissions in street canyons. Boundary-Layer Meteorology 131, 19e34. Guenther, A., Hewitt, C.N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., McKay, W.A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., Zimmermann, P., 1995. A global model of natural volatile organic compound emissions. Journal of Geophysical Research 100, 8873e8892. Hatakeyama, S., Ohno, M., Weng, J., Takagi, H., Akimoto, H., 1987. Mechanism for the formation of gaseous and particulate products from ozone-cycloalkene reactions in air. Environmental Science and Technology 21, 52e57.

41

Ho, K.F., Lee, S.C., Cao, J.J., Kawamura, K., Watanabe, T., Cheng, Y., Chow, J.C., 2006. Dicarboxylic acids, ketacarboxylic acids and dicarbonyls in the urban roadside area of Hong Kong. Atmospheric Environment 40, 3030e3040. Ho, K.F., Cao, J.J., Lee, S.C., Kawamura, K., Zhang, R.J., Chow, J.C., Watson, J.G., 2007. Dicarboxylic acids, ketocarboxylic acids, and dicarbonyls in the urban atmosphere of China. Journal of Geophysical Research 112, D22S27. Hoffmann, T., Odum, J.R., Bowman, F., Collins, D., Klockow, D., Flagan, R.C., Seinfeld, J.H., 1997. Formation of organic aerosols from the oxidation of biogenic hydrocarbons. Journal of Atmospheric Chemistry 26, 189e222. Ion, A.C., Vermeylen, R., Kourtchev, I., Cafmeyer, J., Chi, X., Gelencsér, A., Maenhaut, W., Claeys, M., 2005. Polar organic compounds in rural PM2.5 aerosols from K-puszta, Hungary, during a 2003 summer field campaign: sources and diurnal variations. Atmospheric Chemistry and Physics 5, 1805e1814. Jordan, T.B., Seen, A.J., Jacobsen, G.E., 2006. Levoglucosan as an atmospheric tracer for woodsmoke. Atmospheric Environment 40, 5316e5321. Kawamura, K., Ikushima, K., 1993. Seasonal changes in the distribution of dicarboxylic acids in the urban atmosphere. Environmental Science and Technology 27, 2227e2235. Kawamura, K., Yasui, O., 2005. Diurnal changes in the distribution of dicarboxylic acids, ketocarboxylic acids and dicarbonyls in the urban Tokyo atmosphere. Atmospheric Environment 39, 1945e1960. Kourtchev, I., Ruuskanen, T.M., Maenhaut, W., Kulmala, M., Claeys, M., 2005. Observation of 2-methyltetrols and related photooxidation products of isoprene in boreal forest aerosols from Hyytiälä, Finland. Atmospheric Chemistry and Physics 5, 2761e2770. Kourtchev, I., Ruuskanen, T.M., Keronen, P., Sogacheva, L., Maso, M.D., Reissell, A., Chi, X., Vermeylen, R., Kulmala, M., Maenhaut, W., Claeys, M., 2008a. Determination of isoprene and a-/b-pinene oxidation products in boreal forest aerosols form Hyytiälä, Finland: diel variations and possible link with particle formation events. Plant Biology 10, 138e149. Kourtchev, I., Warnke, J., Maenhaut, W., Hoffmann, T., Claeys, M., 2008b. Polar organic marker compounds in PM2.5 aerosol from a mixed forest site in western Germany. Chemosphere 73, 1308e1314. Kourtchev, I., Copolovici, L., Claeys, M., Maenhaut, W., 2009. Characterization of atmospheric aerosols at a forested site in Central Europe. Environmental Science and Technology 43, 4665e4671. Lamb, B., Guenther, A., Gay, D., Westberg, H., 1987. A national inventory of biogenic hydrocarbon emissions. Atmospheric Environment 21, 1695e1705. Langner, M., Kull, M., Endlicher, W., 2011. Determination of PM10 deposition based on antimony flux to selected urban surfaces. Environmental Pollution 159, 2028e2034. Lewandowski, M., Jaoui, M., Kleindienst, T.E., Offenberg, J.H., Edney, E.O., 2007. Composition of PM2.5 during the summer of 2003 in Research Triangle Park, North Carolina. Atmospheric Environment 41, 4073e4083. Lewandowski, M., Jaoui, M., Offenberg, J.H., Kleindienst, T.E., Edney, E.O., Sheesley, R.J., Schauer, J.J., 2008. Primary and secondary contributions to ambient PM in the midwestern United States. Environmental Science and Technology 42, 3303e3309. Oliveira, C., Pio, C., Alves, C., Evtyugina, M., Santos, P., Goncalves, V., Nunes, T., Silvestre, A.J.D., Palmgren, F., Wâhlin, P., Harrad, S., 2007. Seasonal distribution of polar organic compounds in the urban atmosphere of two large cities from the North and South Europe. Atmospheric Environment 41, 5555e5570. Pashynska, V., Vermeylen, R., Gyorgy, V., Maenhaut, W., Claeys, M., 2002. Development of a gas chromatographic/ion trap mass spectrometric method for the determination of levoglucosan and saccharidic compounds in atmospheric aerosols. Application to urban aerosols. Journal of Mass Spectrometry 37, 1249e1257. Presto, A.A., Huff-Hartz, K.E., Donahue, N.M., 2005. Secondary organic aerosol production from terpene ozonolysis. 1. Effect of UV radiation. Environmental Science and Technology 39, 7036e7045. Puxbaum, H., Caseiro, A., Sánchez-Ochoa, A., Kasper-Giebl, A., Claeys, M., Gelencsér, A., Legrand, M., Preunkert, S., Pio, C., 2007. Levoglucosan levels at background sites in Europe for assessing the impact combustion on the European aerosol background. Journal of Geophysical Research 112, D23S05. Rinne, J., Guenther, A., Greenberg, J., Harley, P.C., 2002. Isoprene and monoterpene fluxes measured above Amazonian rainforest and their dependence on light and temperature. Atmospheric Environment 36, 2421e2426. Rogge, W.F., Hildemann, L.M., Mazurek, M.A., Cass, G.R., Simoneit, B.R.T., 1991. Sources of fine organic aerosol: 1. Charbroilers and meat cooking operations. Environmental Science and Technology 25, 1112e1125. Rogge, W.F., Hildemann, L.M., Mazurek, M.A., Cass, G.R., Simoneit, B.R.T., 1993. Sources of fine organic aerosol. 4. Particulate abrasion products from leaf surfaces of urban plants. Environmental Science and Technology 27, 2700e2711. Röhrl, A., Lammel, G., 2002. Determination of malic acid and other C4 dicarboxylic acids in atmospheric aerosol samples. Chemosphere 46, 1195e1199. Senatsverwaltung für Stadtentwicklung Berlin, 2005. http://fbinter.stadt-berlin.de/ fb/index.jsp?loginkey¼showAreaSelection&mapId¼k07_01verkmeng2005@ senstadt&;areaSelection¼address. Simoneit, B.R.T., Mazurek, M.A., 1982. Organic matter of the troposphere - II. Natural background of biogenic lipid matter in aerosols over the rural western United States. Atmospheric Environment 16, 2139e2159. Simoneit, B.R.T., 1985. Application of molecular marker analysis to vehicular exhaust for source reconciliations. International Journal of Environmental Analytical Chemistry 22, 203e233. Stone, E.A., Zhou, J., Snyder, D.C., Rutter, A.P., Mieritz, M., Schauer, J.J., 2009. A comparison of summertime secondary organic aerosol source contributions

42

S. Wagener et al. / Atmospheric Environment 47 (2012) 33e42

at contrasting urban locations. Environmental Science and Technology 43, 3448e3454. Szidat, S., Jenk, T.M., Gäggeler, H.W., Synal, H.A., Fisseha, R., Baltensperger, U., Kalberer, M., Samburova, V., Reimann, S., Kasper-Giebl, A., Hajdas, I., 2004. Radiocarbon (14C)-deduced biogenic and anthropogenic contributions to organic carbon (OC) of urban aerosols from Zürich, Switzerland. Atmospheric Environment 38, 4035e4044. Tsigaridis, K., Kanakidou, M., 2003. Global modelling of secondary organic aerosol in the troposphere: a sensitivity analysis. Atmospheric Chemistry and Physics 3, 2879e2929. Wang, W., Vas, G., Dommisse, R., Loones, K., Claeys, M., 2004. Fragmentation study of diastereoisomeric 2-methyltetrols, oxidation products of isoprene, as their trimethylsilyl ethers, using gas chromatography/ion trap mass spectrometry. Rapid Communications in Mass Spectrometry 18, 1787e1797. Xia, X., Hopke, P.K., 2006. Seasonal variation of 2-Methyltetrols in ambient air samples. Environmental Science and Technology 40, 6934e6937.

Yan, B., Zheng, M., Hu, Y., Ding, X., Sullivan, A.P., Weber, R.J., Baek, J., Edgerton, E.S., Russell, A.G., 2009. Roadside, urban, and rural comparison of primary and secondary organic molecular markers in ambient PM2.5. Environmental Science and Technology 43, 4287e4293. Yttri, K.E., Dye, C., Kiss, G., 2007. Ambient aerosol concentrations of sugars and sugar-alcohols at four different sites in Norway. Atmospheric Chemistry and Physics 7, 4267e4279. Zhang, Q.H., Birgersson, G., Zhu, J., Löfstedt, C., Löfqvist, J., Schlyter, F., 1999. Leaf volatiles from nonhost deciduous trees: variation by tree species, season and temperature, and electrophysiological activity. Journal of Chemical Ecology 25, 1923e1943. Zhang, Y.Y., Müller, L., Winterhalter, R., Moortgar, G.K., Hoffmann, T., Pöschl, U., 2010. Seasonal cycle and temperature dependence of pinene oxidation products, dicarboxylic acids and nitrophenols in fine and coarse air particulate matter. Atmospheric Chemistry and Physics 10, 7859e7873.