- Email: [email protected]
EC data at a Prague suburban site with 2-h time resolution
Atmospheric Environment 77 (2013) 865e872
Contents lists available at SciVerse ScienceDirect
Atmospheric Environment journal homepage: www.elsevier.com/locate/atmosenv
Analysis of one year’s OC/EC data at a Prague suburban site with 2-h time resolution Petr Vodi cka*, Jaroslav Schwarz, Vladimír Zdímal Institute of Chemical Process Fundamentals of the ASCR, Rozvojová 2/135, 165 02 Prague 6, Suchdol, Czech Republic
h i g h l i g h t s Year’s data on carbonaceous aerosol with 2 h time resolution were analyzed. Diurnal maxima of OC are at night and minima in the afternoon. Significantly different diurnal trends of the EC/TC ratio in summer and winter. Weekly cycles show minimum concentrations on Mondays for both EC and OC. Secondary organic aerosol forms approximately two-thirds of the summer OC.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 14 March 2013 Received in revised form 6 June 2013 Accepted 8 June 2013
The behaviour of elemental and organic carbon (EC and OC) in the atmospheric aerosol fraction PM2.5 was measured at a Prague urban background site in the Czech Republic. The measurements were performed by a semi-online field OC/EC analyzer with a two-hour resolution that sufficiently showed the diurnal variability of OC/EC. The seasonal, daily and diurnal behaviour of the EC and OC were studied using an analysis of the collected data. The results of a one-year campaign (Sep 2009eAug 2010) provide various seasonal patterns of the EC and OC concentrations characteristic for a suburban site in Central Europe. Different sources of carbonaceous aerosols during the various seasons were identified. The winter main sources were probably traffic (mainly EC) and residential heating (both EC and OC). On the other hand, the main EC source in summer is traffic, while the major OC source may be secondary organic aerosols. Winter concentrations were significantly higher than in other seasons. The reason is a combination of stronger air pollution sources in conjunction with poor mixing of the boundary layer. Daily changes of the boundary layer influence the diurnal variations of both EC and OC, too. Afternoon OC concentrations were lower than those at night owing to better daytime atmospheric mixing. The EC late night minima were only slightly lower than the afternoon minima despite much higher traffic in the afternoon. Higher EC concentrations were observed during morning rush hours during all the seasons. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Carbonaceous aerosol Organic carbon Elemental carbon Diurnal variations Seasonal pattern Central Europe
1. Introduction It is known that carbonaceous aerosols usually form the main part of particulate matter and thus significantly contribute to the effects associated with environmental air pollution and climate changes (e.g. Engling and Gelencsér, 2010), lower visibility (e.g. Park et al., 2003) as well as human health (Mauderly and Chow, 2008). These are the main reasons the behaviour and impact of carbonaceous aerosols are studied at different sites all over the world (e.g. Geron, 2009; Lin et al., 2009; von Schneidemesser et al.,
* Corresponding author. E-mail addresses: [email protected] (P. Vodi cka), [email protected] (J. Schwarz). 1352-2310/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atmosenv.2013.06.013
2010). As aerosols contain a complex mixture of organic compounds, their analyses are simplified by measuring the two main parts e the organic and elemental carbon (OC and EC) (e.g. Birch and Cary, 1996). Such a simplification is especially useful when their diurnal trends and long data series are studied. European research projects on ambient carbonaceous aerosols have been carried out mainly in Western Europe (e.g. Viana et al., 2007; Harrison and Yin, 2008) and Scandinavia (Viidanoja et al., 2002; Saarikoski et al., 2008b; Aurela et al., 2011). The EC and OC concentrations in the Central European region have been studied much less (e.g. Puxbaum et al., 2004; Salma et al., 2004). Only a few papers have been published directly from the Prague environment. Sillanpää et al. (2005) and Saarikoski et al. (2008a) studied EC/OC concentrations during one winter campaign (29 Nov 2002e16 Jan
866
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
2003) as a part of the project where PM10 composition was investigated in six European cities. The study of Schwarz et al. (2008) describes the EC and OC in atmospheric aerosols at downtown and suburban sites in Prague which includes all the seasons (during the period 2004e2005). However, these measurements were done in a lower time resolution e only one 24-h sample every third day. This work presents the results from one-year measurements of the EC and OC at a Prague suburban site with a 2-h time resolution, which allows the study of their diurnal behaviour. Such long-term measurements of OC and EC have not yet been conducted in this region. The objective of this paper is to characterize the EC and OC at an urban background site in Central Europe and investigate their seasonal, daily and diurnal behaviours. Another objective is to compare the results from the EC and OC measurements with the meteorology in the area and identify possible sources of carbonaceous aerosol.
Table 1 The modified EUSAAR_2 temperature protocol was used to analyze the samples. Step
Temperature [ C]
Duration [s]
He1 He2 He3 He4 He/Ox.1 He/Ox.2 He/Ox.3 He/Ox.4
200 300 450 640 (650)a 500 550 700 850
90 90 90 135 60 60 60 100
a A temperature of 650 C in the He4 step was used from 11 February to 8 April 2010 and from 24 May to 2 August 2010.
collected) with the following averages: OC ¼ 0.51 0.27 mg m3; EC ¼ 0.01 mg m3. However, the presented data are not blank corrected.
2. Experimental 3. Results and discussion The measurements were conducted at an urban background site located in the northwest suburb of Prague-Suchdol (50 70 36.47300 N, 14 230 5.51300 E, 277 m ASL), on the edge of the plateau above Prague (ca 1.2 million population). The sampling head was installed 5 m above ground on the roof of a sampling container on the campus of the Institute of Chemical Process Fundamentals (ICPF). The distance from the nearest road (10,000e15,000 cars as the daily traffic) is about 250 m. There is no other major road within 1 km of the site. The Václav Havel Airport Prague (hereinafter just “airport”) is at about 9 km to the southwest. The nearest residential houses (heated by gas) are located 30 m southeast and the city centre is located about 5 km in the same direction. The nearest houses using coal and biomass heating are located to the north and northwest in the old district of Prague-Suchdol, the closest is located about 200 m from the site. All in all, local residential heating, traffic from the Prague area, airplane emissions and long-range transport are expected to be the main sources of carbonaceous aerosol at this site. The automatic immission monitoring station (AIM, owner: Czech Hydrometeorological Institute) is located at the ICPF campus 20 m from the sampling point and the data from this station (PM10, trace gases (SO2, NO, NO2, NOx, O3), temperature, humidity, wind speed, wind direction and global radiation) are available. The measurements of the EC and OC were made by a field semionline OC/EC analyzer (Bae et al., 2004) from Sunset Laboratory Inc. (USA) with a PM2.5 cyclone inlet (BGI; flow rate 8 l min1). The device was equipped with a carbon parallel-plate diffusion denuder (from Sunset Lab.) to remove volatile organic compounds that may cause a positive bias in the OC concentrations measured. This semiautomatic device with immediate analysis yields comparable results to laboratory instruments (Aurela et al., 2011; Saarikoski et al., 2008b). The samples were taken at two-hour intervals of which the thermaleoptical analysis takes about 15 min. A shortened EUSAAR_2 protocol (Cavalli et al., 2010) was used; the details of the protocol are shown in Table 1. The collected EC and OC were oxidized to carbon dioxide and analyzed by a non-dispersive infrared (NDIR) detector. Automatic optical corrections for charring were made during each measurement. Control calibrations by sucrose were conducted regularly and instrumental blanks (measured by an automatic reanalysis of the just analyzed filter) were determined twice per day at 0:00 and 12:00 o’clock with the following average values: OC ¼ 0.30 0.20 mg; EC ¼ 0.00 mg (the midday and midnight sample collection were 15 min shorter). Dynamic blanks were also measured by adding a quartz fiber filter that was not prefired (Pall Tissuquartz, filter efficiency 99.97%) upstream of the denuder and using the same sampling time as during the measurement (in total 121 dynamic blank samples were
For this study, one year of data from September 2009 to August 2010 was taken and 3468 measurements covered 79% of the period. Seasonally, 90% of spring is covered (MarcheMay; 989 samples), 77% of summer (JuneAug; 848 samples), 62% of autumn (SepeNov; 677 samples) and 88% of winter (DeceFeb; 954 samples). 21% of the not covered period is because of outages, services or calibrations of the instrument or mainly using the OC/EC analyzer for other campaigns. 3.1. Seasonal trends The time series of total carbon (TC) in Fig. 1 shows the data coverage and higher concentrations of TC during the heating season (winter, partially autumn and spring). The average EC and OC seasonal concentrations as well as the meteorological data are summarized in Table 2. The highest average concentrations of both EC (2.66 mg m3) and OC (9.17 mg m3) were observed during winter, when the average temperature at the site is the lowest (1.8 C). It corresponds with the higher winter concentrations of other pollutants (PM10, SO2, NOx) (Table 2). On the contrary, there was a higher temperature (19.1 C) in summer but much lower concentrations of EC (0.87 mg m3) and OC (3.08 mg m3). Although the average temperature in spring was somewhat lower than in autumn, both EC and OC concentrations were much higher in autumn. It can be explained by the different level of atmospheric mixing due to a much stronger sun influence in spring (Table 2). It seems this seasonal pattern is characteristic for EC and OC at the ICPF site and is similar to the seasonal trend of areas with a large apportioned amount of biomass burning (e.g. von Schneidemesser et al., 2010). In a similar study at a Helsinki suburban site, such a seasonal pattern was not observed (Aurela et al., 2011) even if there is a colder winter than in Prague (Statistical Yearbooks of the Czech Republic and Finland, 2010, 2007). As mentioned by Saarikoski et al. (2008b) the use of coal for domestic combustion is extremely low in Helsinki and it is the probably one of the reasons for the different pattern in the suburbs of Prague. In comparison with the data of Aurela et al. (2011), the yearly average concentrations of both OC (5.6 mg m3) and EC (1.7 mg m3) are much higher in Prague than in Helsinki as can be expected based on a comparison of more than thirty other European sites in Putaud et al. (2010). The PM10 OC/EC data from 2004 of Schwarz et al. (2008) cannot be compared directly to our PM2.5 data, but while OC is comparable with previous data, the EC is much higher. The differences in the thermal protocol used and the increased
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
867
Fig. 1. Time series of total carbon concentrations during entire the campaign.
share of diesel cars in the car fleet may be the reasons for such changes (the number of diesel cars almost tripled between 2000 and 2009 e Transport Statistics of the Czech Republic). The ratio between the EC and OC or TC could be used as a rough indicator characterizing their origin (e.g. Turpin and Huntzicker, 1995). The value of the EC/TC ratio generally depends on many factors such as the analytical method, inlet cut point, artifact correction, method of determining the split point between the EC and OC, and measurement site (Höller et al., 2002). Approximately it holds true that the higher the EC/TC ratio, the higher the contribution of traffic and the lower the EC/TC ratio, the higher the contributions from biomass burning, secondary organics or primary biogenic aerosols. The highest average EC/TC ratio was found in March (0.28, Table A.1). Seasonally, the highest values of EC/TC ratios were during the spring and autumn (0.26, Table 2) in all cases probably due to lower or no residential heating (as compared to winter) and lower photochemical activity (than in summer). The same average EC/TC ratios in both seasons suggest the differences in EC and OC between these two seasons are caused mainly by different levels of dilution (atmospheric mixing) as was mentioned above. On the other hand, the lowest EC/TC ratio was in July (0.21, Table A.1) e a month when the EC emissions from the traffic are lower due to vacations and there is also quite a high level of secondary organic aerosols (SOA) (Yttri et al., 2011) connected with the high photochemical activity in summer and some influence of smaller primary biological particles. This results in seasonally the lowest EC/TC ratio in summer (0.22, Table 2). Forest fires may suppress the EC/TC ratio in summer but they are not common in Central Europe. Some garden barbecues may cause a small decrease of the EC/TC ratio especially during weekends. During winter, the EC/TC ratio 0.24 could be explained by the fact that besides the traffic, an additional source (mainly residential heating) with a lower EC/TC ratio is present (Sillanpää et al., 2005).
A comparison of average months EC and OC concentrations as well as EC/TC ratio, temperatures and radiation are provided in Fig. A.1 and Table A.1. 3.2. Diurnal trends The diurnal trends of the EC, OC and the EC/TC ratio are depicted in Figs. 2AeC, respectively. Fig. 2A shows a typical morning rushhour peak during all of the seasons except winter when there is the broad EC maximum from 8:00 to 14:00. It is similar to the winter EC diurnal trend observed by Aurela et al. (2011). They suggest another EC source in addition to traffic on the basis of NOx diurnal trends. In this work, the EC diurnal trend (Fig. 2A) exhibits a similar trend with NOx which shows its maximum values between 8:00 and 12:00 (Fig. 3A). SO2 shows a broad peak between 10:00 and 16:00 (Fig. 3B) and also has significantly higher concentrations in winter than in the other seasons. Its source is mainly coal burning that is also a source of EC and carbonaceous aerosols. Therefore, the broad EC midday maximum in winter is probably caused by a combination of coal combustion and traffic emissions and their atmospheric transport to the site. The coincidence in time of the EC and SO2 maxima with the maximum of the boundary layer thickness might also suggest the influence of a downdraft of these pollutants from the upper boundary layer to the site and, therefore, the influence of more distant sources emitting pollutants to the higher levels of the boundary layer. Moreover, it was found that the midday maxima of SO2 and EC are more pronounced for those days with lower average concentrations and therefore probably more intense atmospheric mixing, while it is not visible during the days with high concentrations when the mixing is low, mostly due to the existence of an inversion layer. This also suggests a more distant origin of this midday maximum. In this case, Northwest Bohemian coal power plants (part of former so called Black Triangle) might be the source due to the prevailing westerly wind directions. Another
Table 2 The seasonal and annual averages (standard deviation) of the meteorological data, EC/TC ratio and concentrations of OC, EC, PM10 and trace gases. Spring 3
OC [mg m ] EC [mg m3] EC/TC Wind speed [m s1] Temperature [ C] RH % Total radiation [W m2] PM10 [mg m3] SO2 [mg m3] O3 [mg m3] NO [mg m3] NO2 [mg m3] NOx [mg m3]
3.83 1.26 0.26 1.76 8.7 70.8 133 23.5 4.87 62.6 3.10 22.8 27.6
Summer 2.84 0.90 0.08 1.01 6.1 17.1 176 16.1 3.00 25.9 6.21 15.8 22.4
3.08 0.87 0.22 1.30 19.1 70.9 177 18.1 2.65 73.3 1.73 15.7 18.3
1.69 0.61 0.08 0.66 5.2 17.9 214 10.1 2.02 34.8 4.02 11.7 15.7
Autumn 6.08 2.06 0.26 1.53 10.4 78.4 74 26.3 3.53 36.4 7.26 23.1 34.3
5.67 1.79 0.06 0.94 6.0 14.4 127 20.1 2.54 27.0 14.49 13.90 32.16
Winter 9.17 2.66 0.24 1.58 1.8 85.2 37 41.3 10.8 31.2 7.81 36.0 48.0
Annual 6.67 1.84 0.05 0.86 4.8 9.4 74 28.4 9.4 22.3 11.98 19.3 32.8
5.56 1.71 0.24 1.54 9.2 76.2 106 27.1 5.41 51.1 4.88 24.2 31.7
5.24 1.54 0.07 0.89 9.2 16.2 166 21.4 6.03 33.0 10.29 17.0 28.6
868
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
Fig. 2. The average diurnal variation of EC, OC and the EC/TC ratio during different seasons.
not as distant source of SO2 and EC might be airplane emissions (e.g. Starik, 2008) either from the standard landing corridor of the airport above Suchdol or from the airport itself. The highest concentrations of both EC and OC (Fig. 2B) are during the winter evenings and nights when there is the highest need for residential heating. But the main factor for the higher night time aerosol concentrations (not only during winter) is probably on average
Fig. 3. The average diurnal variation of NOx and SO2 during different seasons.
thinner nocturnal mixing boundary layer in comparison with the daylight hours (Stull, 1988). Therefore, regardless of the season, the concentration of the local minima of both EC and OC was found during the afternoon with both the highest temperature and a thicker mixing boundary layer. In comparison with EC, the OC diurnal pattern shows almost no morning peak. This results from the relative importance of other than traffic sources of OC (mainly biomass and coal combustion in winter and secondary organic aerosol formation and primary biogenic aerosol in summer) during all of the seasons at this site. This might happened due to the upwind position of the site with regard to the city for prevailing westerly wind directions and therefore a relatively small influence of the traffic at the site. Thus, the average level of concentrations depends on both the strength of the air pollution sources and the mixing during that period. A combination of both factors results in the lowest concentrations of OC in summer and the highest in winter. The contribution of various sources to both the EC and OC concentrations can be seen much better on the example of the diurnal variations of the EC/TC ratio (Fig. 2C). The morning rush hour peak from 8:00 to 10:00 is distinct in spring, summer and autumn. On the contrary, in winter, there is a broad maximum of the EC/TC ratio across midday; however, the winter 8:00e10:00 EC/ TC value is the lowest morning (8:00e10:00) EC/TC ratio of all the seasons. The winter EC/TC maximum occurs between 14:00 and 16:00 when it achieves the same value as for the spring and autumn. For this reason, it can be derived that the relative traffic influence to the EC had its winter maximum in the afternoon either due to the lowest residential heating and/or due to slower atmospheric mixing and the later transport of urban traffic pollution to the site. On the other hand, the coincidence in time of the EC/TC and SO2 maxima with the maximum of boundary layer thickness might suggest, as is the case for the winter EC midday maximum, that the influence of the downdraft of these pollutants from the upper boundary layer to the site and, therefore, the influence of more distant sources emitting pollutants to the higher layers of the boundary layer (e.g. airplane emissions or coal power plants). Thus, the winter EC/TC ratio trend reflects the poor mixing of the boundary layer as well as the contribution of other sources to the EC emissions than merely traffic. In summer, the morning traffic maximum is evident but the EC/TC ratio rapidly decreases to an afternoon minimum. It can be caused by both strong atmospheric mixing and the contribution of SOA produced in the afternoon when the highest photochemical activity occurs (e.g. Lin et al., 2009). The EC/TC ratio diurnal patterns are very similar in autumn and spring with higher rush-hour maxima than in other seasons. This is owing to similar weather conditions and also the lesser importance of the heating (winter) or SOA (summer) sources. The analogous diurnal patterns of EC/TC in spring and autumn may also suggest a relatively low influence of primary biological particles on PM2.5 OC concentrations because of very different biological processes happening in these seasons. The weekends vs. weekdays yearly averaged diurnal cycle of the EC and OC concentrations are depicted in Fig. 4A and B. Again, there is a clearly visible weekday EC morning rush peak as opposed to weekends (Fig. 4A). The diurnal variations of OC (Fig. 4B) are quite similar and the morning rush-hour peak during weekdays is not as strong (but it is visible) because of other sources of OC. The weekend OC concentrations are even higher than those on weekdays, probably due to greater residential heating and weekend leisure activities (wood burning, garden waste combustion, barbeques etc) in the afternoon and late at night. Similar results with a strong morning EC peak on weekdays caused by traffic and comparable OC trends between weekdays and weekends were observed also by Saarikoski et al. (2008b) in Helsinki.
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
869
Fig. 4. The average diurnal variation of EC and OC during weekdays and weekends.
3.3. Weekly cycle Unlike the natural processes, the weekly cycle should reflect mainly anthropogenic influences. Higher concentrations of OC and especially of EC were observed during weekdays than over weekends in several works (e.g. Lough et al., 2006; Sheesley et al., 2007; Geron, 2009). The largest differences between weekends and weekdays were observed by Dutton et al. (2010) for the EC while for the OC these differences were not so large (even some organic markers showed a higher concentration during weekends). Fig. 5 shows the weekly cycle of the OC and EC for each season at the ICPF site. The annual and spring and summer average weekly cycles are fairly flat but large differences are visible for autumn and winter. However in both cases the differences were proved to be statistically insignificant due to the large variability of the data and the low number of sampling days and in the case of seasonal weakly cycles. A reasoning that partially explains the unusual autumn cycle can be found in the supplementary materials (Text A.1, Fig. A.2). 3.4. Correlations between the EC, OC, gaseous pollutants and meteorological variables The possible relations of the EC and OC to the meteorological variables and gaseous pollutants in different seasons are reflected by the Spearman correlation coefficients listed in Table 3. A stable negative correlation between the EC, OC and wind speed could have been expected during all of the seasons. Both the EC and OC have negative correlations with temperature in winter and autumn, while the summer correlations are positive. On the contrary, positive correlations with relative humidity are the case in winter and autumn and negative in summer. The spring correlation coefficients are weak and insignificant for both the temperature and humidity as well as the correlation coefficients for the total radiation in all the seasons. The correlation with PM10 is always higher for the OC than EC which corresponds to the greater portion of OC (in relation to EC) in PM10 or on the fact that EC is mostly related to PM2.5 and not coarse particles. High correlations of both EC and OC were found with NOx and NO2 during all the seasons. EC always correlates higher than OC with all nitrogen oxides and it confirms their shared origin in combustion processes. The correlation with SO2 is variable during the seasons e it is the strongest in winter
Fig. 5. The average weekly cycle concentrations of the EC and OC during different seasons.
while it is statistically insignificant in summer. These seasonal variations of SO2 roughly follow the heating season when the brown coal with some sulphur content is used (Smolík et al., 1999) for residential heating. The correlations of the different variables with the EC and OC described above might indicate different sources of OC in summer and winter. The concentrations of OC in winter increase with higher humidity (0.26), lower temperature (0.48), and, along with nitrogen oxides, they may be related to a higher concentration of sulphur dioxide (0.59). On the other hand, the summer OC concentrations increase with lower humidity (0.21), higher temperature (0.47), and, moreover, there is a positive correlation of OC with the sum of NO2 and O3 (0.33) that reflects the overall photochemical activity. The correlations discussed above confirm the influence of combustion processes on EC concentrations, both in summer and winter and the influence of residential combustion on OC concentration in winter and the major influence of SOA formation in summer. The still high correlation of OC with NOx in summer may show that part of the SOA in summer is also formed from volatile organic compounds having a similar anthropogenic origin to that of NOx. Similar results were found elsewhere e.g. by Dutton et al. (2010). The analysis of wind directions influence on the concentrations of the EC and OC was performed. Although some of the wind directions give higher EC and OC concentrations than others, it seems that the prevailing meteorological situations connected with a particular wind direction may also influence the OC and EC concentrations. Wind roses are depicted in Fig. A.3 where it is clearly visible that the wind directions at the ICPF site do not depend on the season. The seasonal correlations between OC and EC are depicted in Fig. 6. The highest correlation between EC and OC was in winter (0.93) and autumn (0.91). The lowest correlation (but still high) was observed in summer (0.65) the possible explanation is similar to the summer correlation with NOx (see above). The strong winter and autumn correlations indicate the prevailing presence of
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
870
Table 3 The seasonal Spearman correlation coefficients of EC, respectively OC, with meteorological variables (wind speed, temperature (Temp), relative humidity (RH), total radiation (Rad)), trace gases, PM10 mass and total oxidant levels (NO2 þ O3). s.i. ¼ statistically insignificant.
Annual Spring Summer Autumn Winter
EC OC EC OC EC OC EC OC EC OC
Wind speed
Temp
RH
Rad.
PM10
SO2
O3
NO
NO2
NOx
NO2 þ O3
0.37 0.42 0.43 0.49 0.45 0.47 0.52 0.48 0.58 0.59
0.48 0.42 0.15 s.i. 0.22 0.47 0.34 0.38 0.37 0.48
0.29 0.28 s.i. s.i. 0.09 0.21 0.48 0.50 0.22 0.26
0.21 0.27 0.14 0.24 0.07 0.08 s.i. 0.17 s.i. 0.10
0.76 0.84 0.69 0.78 0.52 0.70 0.77 0.83 0.84 0.90
0.42 0.43 0.32 0.32 s.i. s.i. 0.16 0.20 0.56 0.59
0.62 0.52 0.39 0.32 0.19 0.09 0.72 0.64 0.55 0.55
0.57 0.40 0.21 s.i. 0.36 0.16 0.70 0.55 0.47 0.37
0.87 0.77 0.79 0.72 0.84 0.63 0.83 0.70 0.84 0.77
0.87 0.74 0.77 0.67 0.84 0.61 0.87 0.73 0.82 0.74
0.19 0.12 0.07 0.10 0.09 0.33 0.36 0.35 0.15 0.08
primary sources in the vicinity of the site. On the contrary, the lower correlation in summer indicates some independent OC sources without the presence of EC such as biogenic and secondary organic aerosols (Lin et al., 2009). There are similar slopes of OC/EC fitted lines for the spring and autumn. However, in winter, the slope of the line is substantially higher (ca 3.4) which may indicate the influence of biomass burning. A similar difference between winter and the other seasons can be seen by the determination of the (OC/EC)prim ratio. There is a minimum ratio between the EC and OC, which, under certain conditions described in Castro et al. (1999) or Pio et al. (2011), represent the ratio for primary carbonaceous aerosols (mainly from fossil fuel combustion). The (OC/EC)prim ratio for the whole year is set in Fig. 6 and its values for the seasons are 0.95 for spring, 1.04 for summer, 1.18 for autumn and 1.54 for winter. The established ratio can be used for the calculation of secondary organic carbon (OCsec) using the following equation:
OCsec ¼ OC ðOC=ECÞprim *EC
(1)
As summarized by Pio et al. (2011), Equation (1) is applicable only in cases when there are no aerosols from biomass burning. The ICPF site is burdened with wood-burning emissions during the heating season, which is roughly from mid-October to mid-April (Schwarz et al., 2008). For this reason, the Equation (1) is not applicable for the OCsec calculation during the winter and partially during the autumn and spring, too. On the other hand, this site is rarely exposed to emissions from wildfires so the Equation (1) can be used for the calculation of the summer OCsec formation. The diurnal trends of SOA are depicted in Fig. 7. Based on the analyses of
Fig. 6. A scatter plot of OC vs. EC during different seasons with an estimation of the (OC/EC)prim ratio.
levoglucosan (Schwarz et al., 2011), we know there are biomass combustion events from Friday to Sunday in summer around the ICPF site. Therefore, we calculated the OCsec daily trends separately for MoneThu and FrieSun (Fig. 7) and, indeed, the calculated concentrations of OCsec during the weekend days are higher especially during the late evening and night hours. Thus, the valid summer OCsec diurnal trend at the ICPF station is shown by the Monday-Thursday curve in Fig. 7, and forms approximately twothirds of the summer OC. The minimum OCsec concentrations are in the morning after the expansion of the boundary layer. The OCsec formation begins in the afternoon (when the photochemical activity and mixing of the boundary layer are the most intensive), and the maximum concentrations are reached around midnight. The winter value of (OC/EC)prim is significantly higher than those from other seasons (1.54). It is known that the ratio between the OC and EC from biomass burning sources is much higher (e.g. Gelencsér et al., 2007) than from fossil fuel combustion (e.g. Handler et al., 2008). In this context, it is obvious that emissions of aerosols in winter are elevated by biomass burning. The strong winter correlation between the EC and OC (0.93) thus may reflect their similar main sources at the site. The annual (OC/EC)prim ratio in this work was equal to 1.00 for PM2.5 samples analyzed by the EUSAAR protocol with a 2h resolution. This is in contrary to Schwarz et al. (2008) who determined that the (OC/EC)prim ratio for the ICPF site was 3.44 for PM10 samples analyzed by the NIOSH protocol with a 24h resolution. Such a large difference between these two values shows how important it is to evaluate all of the details in the determination of this ratio. First, Pio et al. (2011) described the reasons for lowering the tendency of (OC/EC)prim ratio from PM10 to PM2.5. Second, the NIOSH protocol systematically measures lower EC concentrations than the EUSAAR protocol (Cavalli et al., 2010;
Fig. 7. The average diurnal variation of the summer OCsec.
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
author’s observation) and thus yields a higher value for the OC/EC ratio. Third, it can be expected that a 2-h sampling has a higher probability that only primary OC is captured than 24-h samples that could collect more secondary aerosols. The sum of all these effects may justify the large difference between the values of the (OC/ EC)prim ratio measured at this station and shows the need for caution in its determination, too. 4. Conclusions The paper studies the behaviour of EC and OC in PM2.5 in a twohour time resolution, and provides the diurnal, weekly, and seasonal OC and EC characteristics found at a suburban site in Prague, Czech Republic. The EC and OC diurnal trends are strongly influenced by the diurnal change of the boundary layer thickness as well as by the time evolution of the strength of both anthropogenic and natural emission sources. It is the main reason that the highest concentrations of both EC and OC were measured in winter and the lowest during summer. While OC has its diurnal maximum during the night (or late evening) in all the seasons, EC exhibits similar maxima in winter and autumn, while it has its diurnal maxima during the morning rush hours in summer and spring due to strong traffic emissions. The night time maxima of EC in winter and autumn are probably caused by the significant impact of residential heating during those seasons and longer nights in comparison to spring. The local EC morning maxima in its diurnal pattern can be found also in autumn and winter. The EC/TC ratio and its diurnal pattern confirm these conclusions having strong maxima at the rush hours in all of the seasons except for winter when this maximum was found in the afternoon probably due to atmospheric transport. On the other hand, the influence of secondary organic aerosol (SOA) of both anthropogenic and biogenic origin can be derived based on the EC/TC minimum in the diurnal pattern in the afternoon in summer. Based on our data, about two thirds of the summer OC concentration is formed by SOA during weekdays. Conversely, the high winter and autumn correlations between OC and EC suggest the prevailing influence of primary sources, i.e. traffic and both coal and biomass combustion for residential heating. The results were confirmed by an analysis of the relation of the OC, EC and EC/TC with other meteorological parameters, or correlations with gaseous pollutants’ concentrations. Acknowledgements Work was supported by the Czech Science Foundation under grants 205/09/2055 and P209/11/1342. We also thank the Czech Hydrometeorological Institute for providing the meteorological data, and Sean Mark Miller, MA, for his correction of the text. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atmosenv.2013.06.013. References Aurela, M., Saarikoski, S., Timonen, H., Aalto, P., Keronen, P., Saarnio, K., Teinilä, K., Kulmala, M., Hillamo, R., 2011. Carbonaceous aerosol at a forested and an urban background sites in Southern Finland. Atmospheric Environment 45, 1394e 1401. Bae, M.-S., Schauer, J.J., DeMinter, J.T., Turner, J.R., Smith, D., Cary, R.A., 2004. Validation of a semi-continuous instrument for elemental carbon and organic carbon using a thermal-optical method. Atmospheric Environment 38 (18), 2885e2893. Birch, M.E., Cary, R.A., 1996. Elemental carbon-based method for monitoring occupational exposures to particulate diesel exhaust. Aerosol Science and Technology 25 (3), 221e241.
871
Castro, L.M., Pio, C.A., Harrison, R.M., Smith, D.J.T., 1999. Carbonaceous aerosol particles in urban and rural European atmospheres: estimation of secondary organic carbon concentrations. Atmospheric Environment 33, 2771e2781. Cavalli, F., Viana, M., Yttri, K.E., Genberg, J., Putaud, J.-P., 2010. Toward a standardized thermal-optical protocol for measuring atmospheric organic and elemental carbon: the EUSAAR protocol. Atmospheric Measurement Techniques 3, 79e89. Dutton, S.J., Rajagopalan, B., Vedal, S., Hannigan, M.P., 2010. Temporal patterns in daily measurements of inorganic and organic speciated PM2.5 in Denver. Atmospheric Environment 44 (7), 987e998. Engling, G., Gelencsér, A., 2010. Atmospheric brown clouds: from local air pollution to climate change. Elements 6 (4), 223e228. Gelencsér, A., May, B., Simpson, D., Sánchez-Ochoa, A., Kasper-Giebl, A., Puxbaum, H., Caseiro, A., Pio, C., Legrand, M., 2007. Source apportionment of PM2.5 organic aerosol over Europe: primary/secondary, natural/anthropogenic, fossil/biogenic origin. Journal of Geophysical Research 112, D23S04. http:// dx.doi.org/10.1029/2006JD008094. Geron, C., 2009. Carbonaceous aerosol over a Pinus taeda forest in Central North Carolina, USA. Atmospheric Environment 43, 959e969. Handler, M., Puls, C., Zbiral, J., Marr, I., Puxbaum, H., Limbeck, A., 2008. Size and composition of particulate emissions from motor vehicles in the KaisermühlenTunnel, Vienna. Atmospheric Environment 42 (9), 2173e2186. Harrison, R.M., Yin, J., 2008. Sources and processes affecting carbonaceous aerosol in central England. Atmospheric Environment 42 (7), 1413e1423. Höller, R., Tohno, S., Kasahara, M., Hitzenberger, R., 2002. Long-term characterization of carbonaceous aerosol in Uji, Japan. Atmospheric Environment 36 (8), 1267e1275. Lin, P., Hu, M., Deng, Z., Slanina, J., Han, S., Kondo, Y., Takegawa, N., Miyazaki, Y., Zhao, Y., Sugimoto, N., 2009. Seasonal and diurnal variations of carbon in PM2.5 in Beijing and the estimation of secondary organic carbon. Journal of Geophysical Research 114, D00G11. http://dx.doi.org/10.1029/2008JD010902. Lough, G.C., Schauer, J.J., Lawson, D.R., 2006. Day-of-week trends in carbonaceous aerosol composition in the urban atmosphere. Atmospheric Environment 40 (22), 4137e4149. Mauderly, J.L., Chow, J.C., 2008. Health effects of organic aerosols. Inhalation Toxicology 20, 257e288. Park, R.J., Jacob, D.J., Chin, M., Martin, R.V., 2003. Sources of carbonaceous aerosols over the United States and implications for natural visibility. Journal of Geophysical Research D: Atmosphere 108, 4355. http://dx.doi.org/10.1029/2002JD003190. Pio, C., Cerqueira, M., Harrison, R.M., Nunes, T., Mirante, F., Alves, C., Oliveira, C., Sanchez, A.C., Artíñano, B., Matos, M., 2011. OC/EC ratio observations in Europe: re-thinking the approach for apportionment between primary and secondary organic carbon. Atmospheric Environment 45 (34), 6121e6132. Putaud, J.-P., et al., 2010. European aerosol phenomenology e 3: physical and chemical characteristics of particulate matter from 60 rural, urban, and kerbside sites across Europe. Atmospheric Environment 44 (10), 1308e1320. Puxbaum, H., Gomiscek, B., Kalina, M., Bauer, H., Salam, A., Stopper, S., Preining, O., Hauck, H., 2004. A dual site study of PM2.5 and PM10 aerosol chemistry in the larger region of Vienna, Austria. Atmospheric Environment 38, 3949e3958. Saarikoski, S.K., Sillanpää, M.K., Saarnio, K.M., Hillamo, R.E., Pennanen, A.S., Salonen, R.O., 2008a. Impact of biomass combustion on urban fine particulate matter in Central and Northern Europe. Water, Air, and Soil Pollution 191 (1e4), 265e277. Saarikoski, S., Timonen, H., Saarnio, K., Aurela, M., Järvi, L., Keronen, P., Kerminen, V.-M., Hillamo, R., 2008b. Sources of organic carbon in fine particulate matter in northern European urban air. Atmospheric Chemistry and Physics 8 (20), 6281e6295. Salma, I., Chi, X., Maenhaut, W., 2004. Elemental and organic carbon in urban canyon and background environments in Budapest, Hungary. Atmospheric Environment 38 (1), 27e36. von Schneidemesser, et al., 2010. Seasonal and spatial trends in the sources of fine particle organic carbon in Israel, Jordan, and Palestine. Atmospheric Environment 44 (30), 3669e3678. Schwarz, J., Chi, X., Maenhaut, W., Civis, M., Hovorka, J., Smolík, J., 2008. Elemental and organic carbon in atmospheric aerosols at downtown and suburban sites in Prague. Atmospheric Research 90, 287e302. Schwarz, J., Karban, J., Chalupní cková, E., Pokorný, R., Novák, J., Smolík, J. The influence of biomass burning on PM2.5 at urban and rural background sites in the Czech Republic (in preparation). Sheesley, R.J., Schauer, J.J., Meiritz, M., DeMinter, J.T., Bae, M.S., Turner, J.R., 2007. Daily variation in particle-phase source tracers in an urban atmosphere. Aerosol Science and Technology 41, 981e993. Sillanpää, M., Frey, A., Hillamo, R., Pennanen, A.S., Salonen, R.O., 2005. Organic, elemental and inorganic carbon in particulate matter of six urban environments in Europe. Atmospheric Chemistry and Physics 5, 2869e2879. Smolík, J., Schwarz, J., Veselý, V., Sýkorová, I., Ku cera, J., Havránek, V., 1999. Characterization of solid emissions from atmospheric fluidized-bed combustion of two Czech lignites. Environmental Science and Technology 33 (20), 3543e3551. Starik, A.M., 2008. Gaseous and particulate emissions with jet engine exhaust and atmospheric pollution. In: Advances on Propulsion Technology for High-speed Aircraft. Educational Notes RTO-EN-AVT-150, Paper 15. RTO, Neuilly-sur-Seine, France, pp. 15-1e15-22. Available from: http://www.rto.nato.int. Statistical Yearbook of the Czech Republic, 2010. Czech Statistical Office. Scientia, Prague. http://www.czso.cz/csu/2011edicniplan.nsf/engpubl/0001-11-2010. Statistical Yearbook of Finland, 2007. ISBN 978-952-467-736-3. Multiprint Oy, Helsinki 2007, http://pxweb2.stat.fi/sahkoiset_julkaisut/vuosikirja2007/pdf/julkaisu.pdf.
872
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
Stull, R.B., 1988. An Introduction to Boundary Layer Meteorology. Kluwer Academic Publisher, Dordrecht, The Netherlands. Transport Statistics of the Czech Republic, 2009. https://www.sydos.cz/cs/rocenka2009/yearbook/htm_uk/uk09_420300.html. Turpin, B.J., Huntzicker, J.J., 1995. Identification of secondary organic aerosol episodes and quantitation of primary and secondary organic aerosol concentrations during SCAQS. Atmospheric Environment 29, 3527e3544. Viana, M., Maenhaut, W., ten Brink, H.M., Chi, X., Weijers, E., Querol, X., Alastuey, A., Mikuska, P., Ve cera, Z., 2007. Comparative analysis of organic and elemental
carbon concentrations in carbonaceous aerosols in three European cities. Atmospheric Environment 41, 5972e5983. Viidanoja, J., Sillanpää, M., Laakia, J., Kerminen, V.M., Hillamo, R., Aarnio, P., Koskentalo, T., 2002. Organic and black carbon in PM2.5 and PM10: 1 year of data from an urban site in Helsinki, Finland. Atmospheric Environment 36, 3183e3193. Yttri, K.E., Simpson, D., Stenström, K., Puxbaum, H., Svendby, T., 2011. Source apportionment of the carbonaceous aerosol in Norway e quantitative estimates based on 14C, thermal-optical and organic tracer analysis. Atmospheric Chemistry and Physics Discussions 11 (3), 7375e7422.
Contents lists available at SciVerse ScienceDirect
Atmospheric Environment journal homepage: www.elsevier.com/locate/atmosenv
Analysis of one year’s OC/EC data at a Prague suburban site with 2-h time resolution Petr Vodi cka*, Jaroslav Schwarz, Vladimír Zdímal Institute of Chemical Process Fundamentals of the ASCR, Rozvojová 2/135, 165 02 Prague 6, Suchdol, Czech Republic
h i g h l i g h t s Year’s data on carbonaceous aerosol with 2 h time resolution were analyzed. Diurnal maxima of OC are at night and minima in the afternoon. Significantly different diurnal trends of the EC/TC ratio in summer and winter. Weekly cycles show minimum concentrations on Mondays for both EC and OC. Secondary organic aerosol forms approximately two-thirds of the summer OC.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 14 March 2013 Received in revised form 6 June 2013 Accepted 8 June 2013
The behaviour of elemental and organic carbon (EC and OC) in the atmospheric aerosol fraction PM2.5 was measured at a Prague urban background site in the Czech Republic. The measurements were performed by a semi-online field OC/EC analyzer with a two-hour resolution that sufficiently showed the diurnal variability of OC/EC. The seasonal, daily and diurnal behaviour of the EC and OC were studied using an analysis of the collected data. The results of a one-year campaign (Sep 2009eAug 2010) provide various seasonal patterns of the EC and OC concentrations characteristic for a suburban site in Central Europe. Different sources of carbonaceous aerosols during the various seasons were identified. The winter main sources were probably traffic (mainly EC) and residential heating (both EC and OC). On the other hand, the main EC source in summer is traffic, while the major OC source may be secondary organic aerosols. Winter concentrations were significantly higher than in other seasons. The reason is a combination of stronger air pollution sources in conjunction with poor mixing of the boundary layer. Daily changes of the boundary layer influence the diurnal variations of both EC and OC, too. Afternoon OC concentrations were lower than those at night owing to better daytime atmospheric mixing. The EC late night minima were only slightly lower than the afternoon minima despite much higher traffic in the afternoon. Higher EC concentrations were observed during morning rush hours during all the seasons. Ó 2013 Elsevier Ltd. All rights reserved.
Keywords: Carbonaceous aerosol Organic carbon Elemental carbon Diurnal variations Seasonal pattern Central Europe
1. Introduction It is known that carbonaceous aerosols usually form the main part of particulate matter and thus significantly contribute to the effects associated with environmental air pollution and climate changes (e.g. Engling and Gelencsér, 2010), lower visibility (e.g. Park et al., 2003) as well as human health (Mauderly and Chow, 2008). These are the main reasons the behaviour and impact of carbonaceous aerosols are studied at different sites all over the world (e.g. Geron, 2009; Lin et al., 2009; von Schneidemesser et al.,
* Corresponding author. E-mail addresses: [email protected] (P. Vodi cka), [email protected] (J. Schwarz). 1352-2310/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atmosenv.2013.06.013
2010). As aerosols contain a complex mixture of organic compounds, their analyses are simplified by measuring the two main parts e the organic and elemental carbon (OC and EC) (e.g. Birch and Cary, 1996). Such a simplification is especially useful when their diurnal trends and long data series are studied. European research projects on ambient carbonaceous aerosols have been carried out mainly in Western Europe (e.g. Viana et al., 2007; Harrison and Yin, 2008) and Scandinavia (Viidanoja et al., 2002; Saarikoski et al., 2008b; Aurela et al., 2011). The EC and OC concentrations in the Central European region have been studied much less (e.g. Puxbaum et al., 2004; Salma et al., 2004). Only a few papers have been published directly from the Prague environment. Sillanpää et al. (2005) and Saarikoski et al. (2008a) studied EC/OC concentrations during one winter campaign (29 Nov 2002e16 Jan
866
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
2003) as a part of the project where PM10 composition was investigated in six European cities. The study of Schwarz et al. (2008) describes the EC and OC in atmospheric aerosols at downtown and suburban sites in Prague which includes all the seasons (during the period 2004e2005). However, these measurements were done in a lower time resolution e only one 24-h sample every third day. This work presents the results from one-year measurements of the EC and OC at a Prague suburban site with a 2-h time resolution, which allows the study of their diurnal behaviour. Such long-term measurements of OC and EC have not yet been conducted in this region. The objective of this paper is to characterize the EC and OC at an urban background site in Central Europe and investigate their seasonal, daily and diurnal behaviours. Another objective is to compare the results from the EC and OC measurements with the meteorology in the area and identify possible sources of carbonaceous aerosol.
Table 1 The modified EUSAAR_2 temperature protocol was used to analyze the samples. Step
Temperature [ C]
Duration [s]
He1 He2 He3 He4 He/Ox.1 He/Ox.2 He/Ox.3 He/Ox.4
200 300 450 640 (650)a 500 550 700 850
90 90 90 135 60 60 60 100
a A temperature of 650 C in the He4 step was used from 11 February to 8 April 2010 and from 24 May to 2 August 2010.
collected) with the following averages: OC ¼ 0.51 0.27 mg m3; EC ¼ 0.01 mg m3. However, the presented data are not blank corrected.
2. Experimental 3. Results and discussion The measurements were conducted at an urban background site located in the northwest suburb of Prague-Suchdol (50 70 36.47300 N, 14 230 5.51300 E, 277 m ASL), on the edge of the plateau above Prague (ca 1.2 million population). The sampling head was installed 5 m above ground on the roof of a sampling container on the campus of the Institute of Chemical Process Fundamentals (ICPF). The distance from the nearest road (10,000e15,000 cars as the daily traffic) is about 250 m. There is no other major road within 1 km of the site. The Václav Havel Airport Prague (hereinafter just “airport”) is at about 9 km to the southwest. The nearest residential houses (heated by gas) are located 30 m southeast and the city centre is located about 5 km in the same direction. The nearest houses using coal and biomass heating are located to the north and northwest in the old district of Prague-Suchdol, the closest is located about 200 m from the site. All in all, local residential heating, traffic from the Prague area, airplane emissions and long-range transport are expected to be the main sources of carbonaceous aerosol at this site. The automatic immission monitoring station (AIM, owner: Czech Hydrometeorological Institute) is located at the ICPF campus 20 m from the sampling point and the data from this station (PM10, trace gases (SO2, NO, NO2, NOx, O3), temperature, humidity, wind speed, wind direction and global radiation) are available. The measurements of the EC and OC were made by a field semionline OC/EC analyzer (Bae et al., 2004) from Sunset Laboratory Inc. (USA) with a PM2.5 cyclone inlet (BGI; flow rate 8 l min1). The device was equipped with a carbon parallel-plate diffusion denuder (from Sunset Lab.) to remove volatile organic compounds that may cause a positive bias in the OC concentrations measured. This semiautomatic device with immediate analysis yields comparable results to laboratory instruments (Aurela et al., 2011; Saarikoski et al., 2008b). The samples were taken at two-hour intervals of which the thermaleoptical analysis takes about 15 min. A shortened EUSAAR_2 protocol (Cavalli et al., 2010) was used; the details of the protocol are shown in Table 1. The collected EC and OC were oxidized to carbon dioxide and analyzed by a non-dispersive infrared (NDIR) detector. Automatic optical corrections for charring were made during each measurement. Control calibrations by sucrose were conducted regularly and instrumental blanks (measured by an automatic reanalysis of the just analyzed filter) were determined twice per day at 0:00 and 12:00 o’clock with the following average values: OC ¼ 0.30 0.20 mg; EC ¼ 0.00 mg (the midday and midnight sample collection were 15 min shorter). Dynamic blanks were also measured by adding a quartz fiber filter that was not prefired (Pall Tissuquartz, filter efficiency 99.97%) upstream of the denuder and using the same sampling time as during the measurement (in total 121 dynamic blank samples were
For this study, one year of data from September 2009 to August 2010 was taken and 3468 measurements covered 79% of the period. Seasonally, 90% of spring is covered (MarcheMay; 989 samples), 77% of summer (JuneAug; 848 samples), 62% of autumn (SepeNov; 677 samples) and 88% of winter (DeceFeb; 954 samples). 21% of the not covered period is because of outages, services or calibrations of the instrument or mainly using the OC/EC analyzer for other campaigns. 3.1. Seasonal trends The time series of total carbon (TC) in Fig. 1 shows the data coverage and higher concentrations of TC during the heating season (winter, partially autumn and spring). The average EC and OC seasonal concentrations as well as the meteorological data are summarized in Table 2. The highest average concentrations of both EC (2.66 mg m3) and OC (9.17 mg m3) were observed during winter, when the average temperature at the site is the lowest (1.8 C). It corresponds with the higher winter concentrations of other pollutants (PM10, SO2, NOx) (Table 2). On the contrary, there was a higher temperature (19.1 C) in summer but much lower concentrations of EC (0.87 mg m3) and OC (3.08 mg m3). Although the average temperature in spring was somewhat lower than in autumn, both EC and OC concentrations were much higher in autumn. It can be explained by the different level of atmospheric mixing due to a much stronger sun influence in spring (Table 2). It seems this seasonal pattern is characteristic for EC and OC at the ICPF site and is similar to the seasonal trend of areas with a large apportioned amount of biomass burning (e.g. von Schneidemesser et al., 2010). In a similar study at a Helsinki suburban site, such a seasonal pattern was not observed (Aurela et al., 2011) even if there is a colder winter than in Prague (Statistical Yearbooks of the Czech Republic and Finland, 2010, 2007). As mentioned by Saarikoski et al. (2008b) the use of coal for domestic combustion is extremely low in Helsinki and it is the probably one of the reasons for the different pattern in the suburbs of Prague. In comparison with the data of Aurela et al. (2011), the yearly average concentrations of both OC (5.6 mg m3) and EC (1.7 mg m3) are much higher in Prague than in Helsinki as can be expected based on a comparison of more than thirty other European sites in Putaud et al. (2010). The PM10 OC/EC data from 2004 of Schwarz et al. (2008) cannot be compared directly to our PM2.5 data, but while OC is comparable with previous data, the EC is much higher. The differences in the thermal protocol used and the increased
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
867
Fig. 1. Time series of total carbon concentrations during entire the campaign.
share of diesel cars in the car fleet may be the reasons for such changes (the number of diesel cars almost tripled between 2000 and 2009 e Transport Statistics of the Czech Republic). The ratio between the EC and OC or TC could be used as a rough indicator characterizing their origin (e.g. Turpin and Huntzicker, 1995). The value of the EC/TC ratio generally depends on many factors such as the analytical method, inlet cut point, artifact correction, method of determining the split point between the EC and OC, and measurement site (Höller et al., 2002). Approximately it holds true that the higher the EC/TC ratio, the higher the contribution of traffic and the lower the EC/TC ratio, the higher the contributions from biomass burning, secondary organics or primary biogenic aerosols. The highest average EC/TC ratio was found in March (0.28, Table A.1). Seasonally, the highest values of EC/TC ratios were during the spring and autumn (0.26, Table 2) in all cases probably due to lower or no residential heating (as compared to winter) and lower photochemical activity (than in summer). The same average EC/TC ratios in both seasons suggest the differences in EC and OC between these two seasons are caused mainly by different levels of dilution (atmospheric mixing) as was mentioned above. On the other hand, the lowest EC/TC ratio was in July (0.21, Table A.1) e a month when the EC emissions from the traffic are lower due to vacations and there is also quite a high level of secondary organic aerosols (SOA) (Yttri et al., 2011) connected with the high photochemical activity in summer and some influence of smaller primary biological particles. This results in seasonally the lowest EC/TC ratio in summer (0.22, Table 2). Forest fires may suppress the EC/TC ratio in summer but they are not common in Central Europe. Some garden barbecues may cause a small decrease of the EC/TC ratio especially during weekends. During winter, the EC/TC ratio 0.24 could be explained by the fact that besides the traffic, an additional source (mainly residential heating) with a lower EC/TC ratio is present (Sillanpää et al., 2005).
A comparison of average months EC and OC concentrations as well as EC/TC ratio, temperatures and radiation are provided in Fig. A.1 and Table A.1. 3.2. Diurnal trends The diurnal trends of the EC, OC and the EC/TC ratio are depicted in Figs. 2AeC, respectively. Fig. 2A shows a typical morning rushhour peak during all of the seasons except winter when there is the broad EC maximum from 8:00 to 14:00. It is similar to the winter EC diurnal trend observed by Aurela et al. (2011). They suggest another EC source in addition to traffic on the basis of NOx diurnal trends. In this work, the EC diurnal trend (Fig. 2A) exhibits a similar trend with NOx which shows its maximum values between 8:00 and 12:00 (Fig. 3A). SO2 shows a broad peak between 10:00 and 16:00 (Fig. 3B) and also has significantly higher concentrations in winter than in the other seasons. Its source is mainly coal burning that is also a source of EC and carbonaceous aerosols. Therefore, the broad EC midday maximum in winter is probably caused by a combination of coal combustion and traffic emissions and their atmospheric transport to the site. The coincidence in time of the EC and SO2 maxima with the maximum of the boundary layer thickness might also suggest the influence of a downdraft of these pollutants from the upper boundary layer to the site and, therefore, the influence of more distant sources emitting pollutants to the higher levels of the boundary layer. Moreover, it was found that the midday maxima of SO2 and EC are more pronounced for those days with lower average concentrations and therefore probably more intense atmospheric mixing, while it is not visible during the days with high concentrations when the mixing is low, mostly due to the existence of an inversion layer. This also suggests a more distant origin of this midday maximum. In this case, Northwest Bohemian coal power plants (part of former so called Black Triangle) might be the source due to the prevailing westerly wind directions. Another
Table 2 The seasonal and annual averages (standard deviation) of the meteorological data, EC/TC ratio and concentrations of OC, EC, PM10 and trace gases. Spring 3
OC [mg m ] EC [mg m3] EC/TC Wind speed [m s1] Temperature [ C] RH % Total radiation [W m2] PM10 [mg m3] SO2 [mg m3] O3 [mg m3] NO [mg m3] NO2 [mg m3] NOx [mg m3]
3.83 1.26 0.26 1.76 8.7 70.8 133 23.5 4.87 62.6 3.10 22.8 27.6
Summer 2.84 0.90 0.08 1.01 6.1 17.1 176 16.1 3.00 25.9 6.21 15.8 22.4
3.08 0.87 0.22 1.30 19.1 70.9 177 18.1 2.65 73.3 1.73 15.7 18.3
1.69 0.61 0.08 0.66 5.2 17.9 214 10.1 2.02 34.8 4.02 11.7 15.7
Autumn 6.08 2.06 0.26 1.53 10.4 78.4 74 26.3 3.53 36.4 7.26 23.1 34.3
5.67 1.79 0.06 0.94 6.0 14.4 127 20.1 2.54 27.0 14.49 13.90 32.16
Winter 9.17 2.66 0.24 1.58 1.8 85.2 37 41.3 10.8 31.2 7.81 36.0 48.0
Annual 6.67 1.84 0.05 0.86 4.8 9.4 74 28.4 9.4 22.3 11.98 19.3 32.8
5.56 1.71 0.24 1.54 9.2 76.2 106 27.1 5.41 51.1 4.88 24.2 31.7
5.24 1.54 0.07 0.89 9.2 16.2 166 21.4 6.03 33.0 10.29 17.0 28.6
868
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
Fig. 2. The average diurnal variation of EC, OC and the EC/TC ratio during different seasons.
not as distant source of SO2 and EC might be airplane emissions (e.g. Starik, 2008) either from the standard landing corridor of the airport above Suchdol or from the airport itself. The highest concentrations of both EC and OC (Fig. 2B) are during the winter evenings and nights when there is the highest need for residential heating. But the main factor for the higher night time aerosol concentrations (not only during winter) is probably on average
Fig. 3. The average diurnal variation of NOx and SO2 during different seasons.
thinner nocturnal mixing boundary layer in comparison with the daylight hours (Stull, 1988). Therefore, regardless of the season, the concentration of the local minima of both EC and OC was found during the afternoon with both the highest temperature and a thicker mixing boundary layer. In comparison with EC, the OC diurnal pattern shows almost no morning peak. This results from the relative importance of other than traffic sources of OC (mainly biomass and coal combustion in winter and secondary organic aerosol formation and primary biogenic aerosol in summer) during all of the seasons at this site. This might happened due to the upwind position of the site with regard to the city for prevailing westerly wind directions and therefore a relatively small influence of the traffic at the site. Thus, the average level of concentrations depends on both the strength of the air pollution sources and the mixing during that period. A combination of both factors results in the lowest concentrations of OC in summer and the highest in winter. The contribution of various sources to both the EC and OC concentrations can be seen much better on the example of the diurnal variations of the EC/TC ratio (Fig. 2C). The morning rush hour peak from 8:00 to 10:00 is distinct in spring, summer and autumn. On the contrary, in winter, there is a broad maximum of the EC/TC ratio across midday; however, the winter 8:00e10:00 EC/ TC value is the lowest morning (8:00e10:00) EC/TC ratio of all the seasons. The winter EC/TC maximum occurs between 14:00 and 16:00 when it achieves the same value as for the spring and autumn. For this reason, it can be derived that the relative traffic influence to the EC had its winter maximum in the afternoon either due to the lowest residential heating and/or due to slower atmospheric mixing and the later transport of urban traffic pollution to the site. On the other hand, the coincidence in time of the EC/TC and SO2 maxima with the maximum of boundary layer thickness might suggest, as is the case for the winter EC midday maximum, that the influence of the downdraft of these pollutants from the upper boundary layer to the site and, therefore, the influence of more distant sources emitting pollutants to the higher layers of the boundary layer (e.g. airplane emissions or coal power plants). Thus, the winter EC/TC ratio trend reflects the poor mixing of the boundary layer as well as the contribution of other sources to the EC emissions than merely traffic. In summer, the morning traffic maximum is evident but the EC/TC ratio rapidly decreases to an afternoon minimum. It can be caused by both strong atmospheric mixing and the contribution of SOA produced in the afternoon when the highest photochemical activity occurs (e.g. Lin et al., 2009). The EC/TC ratio diurnal patterns are very similar in autumn and spring with higher rush-hour maxima than in other seasons. This is owing to similar weather conditions and also the lesser importance of the heating (winter) or SOA (summer) sources. The analogous diurnal patterns of EC/TC in spring and autumn may also suggest a relatively low influence of primary biological particles on PM2.5 OC concentrations because of very different biological processes happening in these seasons. The weekends vs. weekdays yearly averaged diurnal cycle of the EC and OC concentrations are depicted in Fig. 4A and B. Again, there is a clearly visible weekday EC morning rush peak as opposed to weekends (Fig. 4A). The diurnal variations of OC (Fig. 4B) are quite similar and the morning rush-hour peak during weekdays is not as strong (but it is visible) because of other sources of OC. The weekend OC concentrations are even higher than those on weekdays, probably due to greater residential heating and weekend leisure activities (wood burning, garden waste combustion, barbeques etc) in the afternoon and late at night. Similar results with a strong morning EC peak on weekdays caused by traffic and comparable OC trends between weekdays and weekends were observed also by Saarikoski et al. (2008b) in Helsinki.
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
869
Fig. 4. The average diurnal variation of EC and OC during weekdays and weekends.
3.3. Weekly cycle Unlike the natural processes, the weekly cycle should reflect mainly anthropogenic influences. Higher concentrations of OC and especially of EC were observed during weekdays than over weekends in several works (e.g. Lough et al., 2006; Sheesley et al., 2007; Geron, 2009). The largest differences between weekends and weekdays were observed by Dutton et al. (2010) for the EC while for the OC these differences were not so large (even some organic markers showed a higher concentration during weekends). Fig. 5 shows the weekly cycle of the OC and EC for each season at the ICPF site. The annual and spring and summer average weekly cycles are fairly flat but large differences are visible for autumn and winter. However in both cases the differences were proved to be statistically insignificant due to the large variability of the data and the low number of sampling days and in the case of seasonal weakly cycles. A reasoning that partially explains the unusual autumn cycle can be found in the supplementary materials (Text A.1, Fig. A.2). 3.4. Correlations between the EC, OC, gaseous pollutants and meteorological variables The possible relations of the EC and OC to the meteorological variables and gaseous pollutants in different seasons are reflected by the Spearman correlation coefficients listed in Table 3. A stable negative correlation between the EC, OC and wind speed could have been expected during all of the seasons. Both the EC and OC have negative correlations with temperature in winter and autumn, while the summer correlations are positive. On the contrary, positive correlations with relative humidity are the case in winter and autumn and negative in summer. The spring correlation coefficients are weak and insignificant for both the temperature and humidity as well as the correlation coefficients for the total radiation in all the seasons. The correlation with PM10 is always higher for the OC than EC which corresponds to the greater portion of OC (in relation to EC) in PM10 or on the fact that EC is mostly related to PM2.5 and not coarse particles. High correlations of both EC and OC were found with NOx and NO2 during all the seasons. EC always correlates higher than OC with all nitrogen oxides and it confirms their shared origin in combustion processes. The correlation with SO2 is variable during the seasons e it is the strongest in winter
Fig. 5. The average weekly cycle concentrations of the EC and OC during different seasons.
while it is statistically insignificant in summer. These seasonal variations of SO2 roughly follow the heating season when the brown coal with some sulphur content is used (Smolík et al., 1999) for residential heating. The correlations of the different variables with the EC and OC described above might indicate different sources of OC in summer and winter. The concentrations of OC in winter increase with higher humidity (0.26), lower temperature (0.48), and, along with nitrogen oxides, they may be related to a higher concentration of sulphur dioxide (0.59). On the other hand, the summer OC concentrations increase with lower humidity (0.21), higher temperature (0.47), and, moreover, there is a positive correlation of OC with the sum of NO2 and O3 (0.33) that reflects the overall photochemical activity. The correlations discussed above confirm the influence of combustion processes on EC concentrations, both in summer and winter and the influence of residential combustion on OC concentration in winter and the major influence of SOA formation in summer. The still high correlation of OC with NOx in summer may show that part of the SOA in summer is also formed from volatile organic compounds having a similar anthropogenic origin to that of NOx. Similar results were found elsewhere e.g. by Dutton et al. (2010). The analysis of wind directions influence on the concentrations of the EC and OC was performed. Although some of the wind directions give higher EC and OC concentrations than others, it seems that the prevailing meteorological situations connected with a particular wind direction may also influence the OC and EC concentrations. Wind roses are depicted in Fig. A.3 where it is clearly visible that the wind directions at the ICPF site do not depend on the season. The seasonal correlations between OC and EC are depicted in Fig. 6. The highest correlation between EC and OC was in winter (0.93) and autumn (0.91). The lowest correlation (but still high) was observed in summer (0.65) the possible explanation is similar to the summer correlation with NOx (see above). The strong winter and autumn correlations indicate the prevailing presence of
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
870
Table 3 The seasonal Spearman correlation coefficients of EC, respectively OC, with meteorological variables (wind speed, temperature (Temp), relative humidity (RH), total radiation (Rad)), trace gases, PM10 mass and total oxidant levels (NO2 þ O3). s.i. ¼ statistically insignificant.
Annual Spring Summer Autumn Winter
EC OC EC OC EC OC EC OC EC OC
Wind speed
Temp
RH
Rad.
PM10
SO2
O3
NO
NO2
NOx
NO2 þ O3
0.37 0.42 0.43 0.49 0.45 0.47 0.52 0.48 0.58 0.59
0.48 0.42 0.15 s.i. 0.22 0.47 0.34 0.38 0.37 0.48
0.29 0.28 s.i. s.i. 0.09 0.21 0.48 0.50 0.22 0.26
0.21 0.27 0.14 0.24 0.07 0.08 s.i. 0.17 s.i. 0.10
0.76 0.84 0.69 0.78 0.52 0.70 0.77 0.83 0.84 0.90
0.42 0.43 0.32 0.32 s.i. s.i. 0.16 0.20 0.56 0.59
0.62 0.52 0.39 0.32 0.19 0.09 0.72 0.64 0.55 0.55
0.57 0.40 0.21 s.i. 0.36 0.16 0.70 0.55 0.47 0.37
0.87 0.77 0.79 0.72 0.84 0.63 0.83 0.70 0.84 0.77
0.87 0.74 0.77 0.67 0.84 0.61 0.87 0.73 0.82 0.74
0.19 0.12 0.07 0.10 0.09 0.33 0.36 0.35 0.15 0.08
primary sources in the vicinity of the site. On the contrary, the lower correlation in summer indicates some independent OC sources without the presence of EC such as biogenic and secondary organic aerosols (Lin et al., 2009). There are similar slopes of OC/EC fitted lines for the spring and autumn. However, in winter, the slope of the line is substantially higher (ca 3.4) which may indicate the influence of biomass burning. A similar difference between winter and the other seasons can be seen by the determination of the (OC/EC)prim ratio. There is a minimum ratio between the EC and OC, which, under certain conditions described in Castro et al. (1999) or Pio et al. (2011), represent the ratio for primary carbonaceous aerosols (mainly from fossil fuel combustion). The (OC/EC)prim ratio for the whole year is set in Fig. 6 and its values for the seasons are 0.95 for spring, 1.04 for summer, 1.18 for autumn and 1.54 for winter. The established ratio can be used for the calculation of secondary organic carbon (OCsec) using the following equation:
OCsec ¼ OC ðOC=ECÞprim *EC
(1)
As summarized by Pio et al. (2011), Equation (1) is applicable only in cases when there are no aerosols from biomass burning. The ICPF site is burdened with wood-burning emissions during the heating season, which is roughly from mid-October to mid-April (Schwarz et al., 2008). For this reason, the Equation (1) is not applicable for the OCsec calculation during the winter and partially during the autumn and spring, too. On the other hand, this site is rarely exposed to emissions from wildfires so the Equation (1) can be used for the calculation of the summer OCsec formation. The diurnal trends of SOA are depicted in Fig. 7. Based on the analyses of
Fig. 6. A scatter plot of OC vs. EC during different seasons with an estimation of the (OC/EC)prim ratio.
levoglucosan (Schwarz et al., 2011), we know there are biomass combustion events from Friday to Sunday in summer around the ICPF site. Therefore, we calculated the OCsec daily trends separately for MoneThu and FrieSun (Fig. 7) and, indeed, the calculated concentrations of OCsec during the weekend days are higher especially during the late evening and night hours. Thus, the valid summer OCsec diurnal trend at the ICPF station is shown by the Monday-Thursday curve in Fig. 7, and forms approximately twothirds of the summer OC. The minimum OCsec concentrations are in the morning after the expansion of the boundary layer. The OCsec formation begins in the afternoon (when the photochemical activity and mixing of the boundary layer are the most intensive), and the maximum concentrations are reached around midnight. The winter value of (OC/EC)prim is significantly higher than those from other seasons (1.54). It is known that the ratio between the OC and EC from biomass burning sources is much higher (e.g. Gelencsér et al., 2007) than from fossil fuel combustion (e.g. Handler et al., 2008). In this context, it is obvious that emissions of aerosols in winter are elevated by biomass burning. The strong winter correlation between the EC and OC (0.93) thus may reflect their similar main sources at the site. The annual (OC/EC)prim ratio in this work was equal to 1.00 for PM2.5 samples analyzed by the EUSAAR protocol with a 2h resolution. This is in contrary to Schwarz et al. (2008) who determined that the (OC/EC)prim ratio for the ICPF site was 3.44 for PM10 samples analyzed by the NIOSH protocol with a 24h resolution. Such a large difference between these two values shows how important it is to evaluate all of the details in the determination of this ratio. First, Pio et al. (2011) described the reasons for lowering the tendency of (OC/EC)prim ratio from PM10 to PM2.5. Second, the NIOSH protocol systematically measures lower EC concentrations than the EUSAAR protocol (Cavalli et al., 2010;
Fig. 7. The average diurnal variation of the summer OCsec.
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
author’s observation) and thus yields a higher value for the OC/EC ratio. Third, it can be expected that a 2-h sampling has a higher probability that only primary OC is captured than 24-h samples that could collect more secondary aerosols. The sum of all these effects may justify the large difference between the values of the (OC/ EC)prim ratio measured at this station and shows the need for caution in its determination, too. 4. Conclusions The paper studies the behaviour of EC and OC in PM2.5 in a twohour time resolution, and provides the diurnal, weekly, and seasonal OC and EC characteristics found at a suburban site in Prague, Czech Republic. The EC and OC diurnal trends are strongly influenced by the diurnal change of the boundary layer thickness as well as by the time evolution of the strength of both anthropogenic and natural emission sources. It is the main reason that the highest concentrations of both EC and OC were measured in winter and the lowest during summer. While OC has its diurnal maximum during the night (or late evening) in all the seasons, EC exhibits similar maxima in winter and autumn, while it has its diurnal maxima during the morning rush hours in summer and spring due to strong traffic emissions. The night time maxima of EC in winter and autumn are probably caused by the significant impact of residential heating during those seasons and longer nights in comparison to spring. The local EC morning maxima in its diurnal pattern can be found also in autumn and winter. The EC/TC ratio and its diurnal pattern confirm these conclusions having strong maxima at the rush hours in all of the seasons except for winter when this maximum was found in the afternoon probably due to atmospheric transport. On the other hand, the influence of secondary organic aerosol (SOA) of both anthropogenic and biogenic origin can be derived based on the EC/TC minimum in the diurnal pattern in the afternoon in summer. Based on our data, about two thirds of the summer OC concentration is formed by SOA during weekdays. Conversely, the high winter and autumn correlations between OC and EC suggest the prevailing influence of primary sources, i.e. traffic and both coal and biomass combustion for residential heating. The results were confirmed by an analysis of the relation of the OC, EC and EC/TC with other meteorological parameters, or correlations with gaseous pollutants’ concentrations. Acknowledgements Work was supported by the Czech Science Foundation under grants 205/09/2055 and P209/11/1342. We also thank the Czech Hydrometeorological Institute for providing the meteorological data, and Sean Mark Miller, MA, for his correction of the text. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atmosenv.2013.06.013. References Aurela, M., Saarikoski, S., Timonen, H., Aalto, P., Keronen, P., Saarnio, K., Teinilä, K., Kulmala, M., Hillamo, R., 2011. Carbonaceous aerosol at a forested and an urban background sites in Southern Finland. Atmospheric Environment 45, 1394e 1401. Bae, M.-S., Schauer, J.J., DeMinter, J.T., Turner, J.R., Smith, D., Cary, R.A., 2004. Validation of a semi-continuous instrument for elemental carbon and organic carbon using a thermal-optical method. Atmospheric Environment 38 (18), 2885e2893. Birch, M.E., Cary, R.A., 1996. Elemental carbon-based method for monitoring occupational exposures to particulate diesel exhaust. Aerosol Science and Technology 25 (3), 221e241.
871
Castro, L.M., Pio, C.A., Harrison, R.M., Smith, D.J.T., 1999. Carbonaceous aerosol particles in urban and rural European atmospheres: estimation of secondary organic carbon concentrations. Atmospheric Environment 33, 2771e2781. Cavalli, F., Viana, M., Yttri, K.E., Genberg, J., Putaud, J.-P., 2010. Toward a standardized thermal-optical protocol for measuring atmospheric organic and elemental carbon: the EUSAAR protocol. Atmospheric Measurement Techniques 3, 79e89. Dutton, S.J., Rajagopalan, B., Vedal, S., Hannigan, M.P., 2010. Temporal patterns in daily measurements of inorganic and organic speciated PM2.5 in Denver. Atmospheric Environment 44 (7), 987e998. Engling, G., Gelencsér, A., 2010. Atmospheric brown clouds: from local air pollution to climate change. Elements 6 (4), 223e228. Gelencsér, A., May, B., Simpson, D., Sánchez-Ochoa, A., Kasper-Giebl, A., Puxbaum, H., Caseiro, A., Pio, C., Legrand, M., 2007. Source apportionment of PM2.5 organic aerosol over Europe: primary/secondary, natural/anthropogenic, fossil/biogenic origin. Journal of Geophysical Research 112, D23S04. http:// dx.doi.org/10.1029/2006JD008094. Geron, C., 2009. Carbonaceous aerosol over a Pinus taeda forest in Central North Carolina, USA. Atmospheric Environment 43, 959e969. Handler, M., Puls, C., Zbiral, J., Marr, I., Puxbaum, H., Limbeck, A., 2008. Size and composition of particulate emissions from motor vehicles in the KaisermühlenTunnel, Vienna. Atmospheric Environment 42 (9), 2173e2186. Harrison, R.M., Yin, J., 2008. Sources and processes affecting carbonaceous aerosol in central England. Atmospheric Environment 42 (7), 1413e1423. Höller, R., Tohno, S., Kasahara, M., Hitzenberger, R., 2002. Long-term characterization of carbonaceous aerosol in Uji, Japan. Atmospheric Environment 36 (8), 1267e1275. Lin, P., Hu, M., Deng, Z., Slanina, J., Han, S., Kondo, Y., Takegawa, N., Miyazaki, Y., Zhao, Y., Sugimoto, N., 2009. Seasonal and diurnal variations of carbon in PM2.5 in Beijing and the estimation of secondary organic carbon. Journal of Geophysical Research 114, D00G11. http://dx.doi.org/10.1029/2008JD010902. Lough, G.C., Schauer, J.J., Lawson, D.R., 2006. Day-of-week trends in carbonaceous aerosol composition in the urban atmosphere. Atmospheric Environment 40 (22), 4137e4149. Mauderly, J.L., Chow, J.C., 2008. Health effects of organic aerosols. Inhalation Toxicology 20, 257e288. Park, R.J., Jacob, D.J., Chin, M., Martin, R.V., 2003. Sources of carbonaceous aerosols over the United States and implications for natural visibility. Journal of Geophysical Research D: Atmosphere 108, 4355. http://dx.doi.org/10.1029/2002JD003190. Pio, C., Cerqueira, M., Harrison, R.M., Nunes, T., Mirante, F., Alves, C., Oliveira, C., Sanchez, A.C., Artíñano, B., Matos, M., 2011. OC/EC ratio observations in Europe: re-thinking the approach for apportionment between primary and secondary organic carbon. Atmospheric Environment 45 (34), 6121e6132. Putaud, J.-P., et al., 2010. European aerosol phenomenology e 3: physical and chemical characteristics of particulate matter from 60 rural, urban, and kerbside sites across Europe. Atmospheric Environment 44 (10), 1308e1320. Puxbaum, H., Gomiscek, B., Kalina, M., Bauer, H., Salam, A., Stopper, S., Preining, O., Hauck, H., 2004. A dual site study of PM2.5 and PM10 aerosol chemistry in the larger region of Vienna, Austria. Atmospheric Environment 38, 3949e3958. Saarikoski, S.K., Sillanpää, M.K., Saarnio, K.M., Hillamo, R.E., Pennanen, A.S., Salonen, R.O., 2008a. Impact of biomass combustion on urban fine particulate matter in Central and Northern Europe. Water, Air, and Soil Pollution 191 (1e4), 265e277. Saarikoski, S., Timonen, H., Saarnio, K., Aurela, M., Järvi, L., Keronen, P., Kerminen, V.-M., Hillamo, R., 2008b. Sources of organic carbon in fine particulate matter in northern European urban air. Atmospheric Chemistry and Physics 8 (20), 6281e6295. Salma, I., Chi, X., Maenhaut, W., 2004. Elemental and organic carbon in urban canyon and background environments in Budapest, Hungary. Atmospheric Environment 38 (1), 27e36. von Schneidemesser, et al., 2010. Seasonal and spatial trends in the sources of fine particle organic carbon in Israel, Jordan, and Palestine. Atmospheric Environment 44 (30), 3669e3678. Schwarz, J., Chi, X., Maenhaut, W., Civis, M., Hovorka, J., Smolík, J., 2008. Elemental and organic carbon in atmospheric aerosols at downtown and suburban sites in Prague. Atmospheric Research 90, 287e302. Schwarz, J., Karban, J., Chalupní cková, E., Pokorný, R., Novák, J., Smolík, J. The influence of biomass burning on PM2.5 at urban and rural background sites in the Czech Republic (in preparation). Sheesley, R.J., Schauer, J.J., Meiritz, M., DeMinter, J.T., Bae, M.S., Turner, J.R., 2007. Daily variation in particle-phase source tracers in an urban atmosphere. Aerosol Science and Technology 41, 981e993. Sillanpää, M., Frey, A., Hillamo, R., Pennanen, A.S., Salonen, R.O., 2005. Organic, elemental and inorganic carbon in particulate matter of six urban environments in Europe. Atmospheric Chemistry and Physics 5, 2869e2879. Smolík, J., Schwarz, J., Veselý, V., Sýkorová, I., Ku cera, J., Havránek, V., 1999. Characterization of solid emissions from atmospheric fluidized-bed combustion of two Czech lignites. Environmental Science and Technology 33 (20), 3543e3551. Starik, A.M., 2008. Gaseous and particulate emissions with jet engine exhaust and atmospheric pollution. In: Advances on Propulsion Technology for High-speed Aircraft. Educational Notes RTO-EN-AVT-150, Paper 15. RTO, Neuilly-sur-Seine, France, pp. 15-1e15-22. Available from: http://www.rto.nato.int. Statistical Yearbook of the Czech Republic, 2010. Czech Statistical Office. Scientia, Prague. http://www.czso.cz/csu/2011edicniplan.nsf/engpubl/0001-11-2010. Statistical Yearbook of Finland, 2007. ISBN 978-952-467-736-3. Multiprint Oy, Helsinki 2007, http://pxweb2.stat.fi/sahkoiset_julkaisut/vuosikirja2007/pdf/julkaisu.pdf.
872
P. Vodicka et al. / Atmospheric Environment 77 (2013) 865e872
Stull, R.B., 1988. An Introduction to Boundary Layer Meteorology. Kluwer Academic Publisher, Dordrecht, The Netherlands. Transport Statistics of the Czech Republic, 2009. https://www.sydos.cz/cs/rocenka2009/yearbook/htm_uk/uk09_420300.html. Turpin, B.J., Huntzicker, J.J., 1995. Identification of secondary organic aerosol episodes and quantitation of primary and secondary organic aerosol concentrations during SCAQS. Atmospheric Environment 29, 3527e3544. Viana, M., Maenhaut, W., ten Brink, H.M., Chi, X., Weijers, E., Querol, X., Alastuey, A., Mikuska, P., Ve cera, Z., 2007. Comparative analysis of organic and elemental
carbon concentrations in carbonaceous aerosols in three European cities. Atmospheric Environment 41, 5972e5983. Viidanoja, J., Sillanpää, M., Laakia, J., Kerminen, V.M., Hillamo, R., Aarnio, P., Koskentalo, T., 2002. Organic and black carbon in PM2.5 and PM10: 1 year of data from an urban site in Helsinki, Finland. Atmospheric Environment 36, 3183e3193. Yttri, K.E., Simpson, D., Stenström, K., Puxbaum, H., Svendby, T., 2011. Source apportionment of the carbonaceous aerosol in Norway e quantitative estimates based on 14C, thermal-optical and organic tracer analysis. Atmospheric Chemistry and Physics Discussions 11 (3), 7375e7422.