Introduction
New aerosol particle formation (NPF) and consecutive particle growth
processes in the atmosphere (Kulmala et al., 2013) were first identified in
clean environments (Weber et al., 1995; Mäkelä et al., 1997), and the
NPF occurrence frequency and its contribution to particle number
concentrations were later found to be substantial in the global troposphere
(Kulmala et al., 2004; Spracklen et al., 2006). Particles originating from
these processes affect the Earth's radiation balance mainly by acting as
cloud condensation nuclei (CCN; Kerminen et al., 2012; Carslaw et al., 2013),
and their contribution to the total number of CCN can be up to 50 % or
even more (Merikanto et al., 2009). Recently, NPF has been proved to be common
in polluted environments, including large cities (Woo et al., 2001;
Baltensperger et al., 2002; Alam et al., 2003; Wehner et al., 2004; Salma et
al., 2011; Dall'Osto et al., 2013; Xiao et al., 2015) as well. The
connections between the urban and regional air, including air pollution and
climate, have remained unknown despite the fact that NPF and particle growth
driven by regional air masses can also interact with urban climate and can
contribute to the public's excess health risk from nanoparticle exposure
(Salma et al., 2014, 2015).
The Carpathian Basin offers excellent conditions for atmospheric studies on
interactions between regional and urban NPF processes because of its
extension, moderate climate and topographically discrete character and
because it contains a large city, Budapest, at its central part. We
characterized atmospheric conditions of the city centre and near-city
background of Budapest by performing continuous measurements of aerosol, air
pollutant gases and meteorological data for two 1-year-long time intervals.
We completed similar measurements in the rural background at the K-puszta
station, representing the regional atmospheric conditions over the same time
intervals. The major objectives of the present paper are to identify and
quantify both important similarities and differences between the urban and
regional NPF types and to investigate the interactions and associations
between urban air in Budapest and regional rural atmosphere in the background
of the city with respect to NPF.
Image of the Carpathian Basin in central Europe retrieved
from Aqua/MODIS data indicating the location and advantages of a well-separated basin (marked by black curve) and of the measurement sites in
Budapest and at the K-puszta station (shown by blue and green dots,
respectively).
Methods
Measurement locations and time intervals
The Carpathian Basin (also known as the Pannonian Basin) is a topographically
discrete unit in the south-eastern part of central Europe surrounded by the
Eastern Alps, the Carpathian Mountains, the Balkan Mountains and the Dinaric
Alps (Karátson, 2006; Fig. 1). Its typical dimensions in the N–S and
W–E directions are approximately 450 and 650 km, respectively, with a
territory of approximately 330 thousand km2. Three climate zones,
namely maritime temperate (typical for the mainland), warm summer continental
(typical for the eastern-central part) and Mediterranean (typical for the
southern part) climate zones, meet in the region. The annual insolation is
4200–4700 MJ m-2, with a maximum in the central part (Spinoni et al.,
2014). The annual sunshine duration is between 1850 and 2200 h, which
results in an annual relative sunshine duration of 40–47 %, with a
minimum of 15–20 % in December and a maximum of 55–65 % in August.
The annual mean air temperature at the sea level is approximately
10 ∘C, which is higher by about 2.5 ∘C than the global
annual mean temperature for corresponding latitudes. There are differences of up
to 3–4 ∘C in the annual mean temperatures among various subbasins.
The mean temperature range is substantial; its annual mean is between 21 and
26 ∘C and has
a tendency to increase to the E due to the influence of the continental climate zone. The annual mean rainfall in the lowland is
between 600 and 700 mm, with a minimum in the central part of the territory.
The Carpathian Basin is located in the belt of the prevailing westerly winds.
The bounding mountains, however, represent important barriers to the global
wind pattern. The wind directions and speeds within the basin are
substantially modified by passing weather systems, inner mountains and local
radiation gradients. As a result, the surface westerly winds arriving at the
basin are usually spread to N winds prevailing in the western part and to NW
winds occurring especially in the upper central part of the basin. In the
southern part of the Great Hungarian Plain, southerly winds often occur,
while in the eastern part of the basin, the prevailing wind directions are NE
or N particularly in winter. The annual mean wind speed at the height of
10 m is between 2 and 4 m s-1, with smaller values in autumn and
larger values in spring. Weather situations within the basin are generally
uniform. For some limited time intervals, rather distinct weather conditions
can be realized in the different territories of the basin due to the
geographical, meteorological and climate properties and features mentioned
above. The land of the basin is mostly used for intensive agriculture and
farming, and larger forested areas with deciduous, coniferous or mixed wood
occur in the inner and bounding mountains. The total number of inhabitants in
the basin is estimated to be 26 million, and its largest city is Budapest
with 2.5 million inhabitants in the metropolitan area.
The data evaluated in the present study were obtained in the Budapest and at
the K-puszta measurement stations (Fig. 1). The geographical area between the two
sites is plain. The measurements in Budapest were carried out continuously in the central
part of the city (Lágymányos Campus of the Eötvös University;
47.474∘ N, 19.062∘ E; 114 m above mean sea level, a.m.s.l.) in
an open area near the river Danube from 3 November 2008 to
2 November 2009 (Salma et al., 2011, 2016).
The location represents well-mixed urban air in the city centre. Another
1-year-long continuous measurement campaign was realized at the NW border of
Budapest in a wooded area (Konkoly Astronomical Observatory of the Hungarian
Academy of Sciences; 47.500∘ N, 18.963∘ E; 478 m a.m.s.l.)
from 19 January 2012 to 18 January 2013. This site represents the near-city
background. The K-puszta measurement station (46.967∘ N,
19.586∘ E; 127 m a.m.s.l.) is situated on the Great Hungarian Plain
at a distance of 71 km from and to the SE of Budapest. The station is located in a forest
clearing with its near-scale surroundings dominated by mixed forest (62 %
coniferous, 28 % deciduous) and grassland (10 %). The station
represents the rural background. It is involved in the European Monitoring
and Evaluation Programme (EMEP station no. HU0002R). Two 1-year-long data
sets which correspond exactly to those considered for Budapest were selected
for the evaluations.
Measurements
The principal measuring system was a flow-switching type differential
mobility particle sizer (DMPS) at both sites. Its main components are a
radioactive bipolar charger, a Nafion semipermeable membrane dryer, a
differential mobility analyser and a butanol-based condensation particle
counter (TSI CPC3775 in Budapest and CPC3772 at the K-puszta station; Aalto et
al., 2001). Particles with an electrical mobility diameter from 6 to 1000 nm
(Budapest) and from 6 to 800 nm (K-puszta, for most of the time) are
recorded in their dry state in 30 channels. The sample flow was
2.0 L min-1 (Budapest) or 1.0 L min-1 (K-puszta) in the
high-flow mode and 0.3 L min-1 in the low-flow mode. The time
resolution of the measurement was approximately 10 min. There was no upper
size cut-off inlet applied to the sampling lines, so that only a weather shield
and insect net were attached. The DMPS measurements were performed
according to the international technical standard (Wiedensohler et al.,
2012). Synoptic meteorological data were obtained from regular measurement
stations of the Hungarian Meteorological Service operated in Budapest
(no. 12843) and at the military airport in Kecskemét (no. 12970).
Standardized meteorological measurements of air temperature (T), relative
humidity (RH), wind speed (WS), wind direction (WD) and cloudiness (n) are
recorded at these stations with a time resolution of 1 h. Global radiation
(GRad) was calculated from the measured meteorological data using the method of
Holtslag and Van Ulden (Foken, 2006; Weidinger et al., 2008). The planetary
boundary layer (PBL) height was obtained from the ECMWF Integral Forecast
System based on the ERA-Interim reanalysis, with a spatial resolution of
0.5∘ × 0.5∘ and a time resolution of 3 h (Dee et al.,
2011). Concentrations of atmospheric criteria pollutants were obtained from
the closest measurement station of the National Air Quality Network in
Budapest (at a distance of 1.6 km from the urban site and of 6.9 km from
the near-city background site) and in Százhalombatta (at a distance of
63 km) for the K-puszta station; all are located in the prevailing upwind direction
from the measurement sites. The concentration of SO2 in Budapest is
ordinary distributed without larger spatial differences (Salma et al., 2016).
Ozone and PM10 mass were recorded directly at the K-puszta station.
Standardized measurements of SO2 (by UV fluorescence, Ysselbach 43C),
PM10 mass (by beta-ray absorption, Thermo FH62-I-R) and O3 (by UV
absorption, Ysselbach 49C) with a time resolution of 1 h are performed at
the stations. The DMPS data in Budapest and at the K-puszta station were
available for more than 90 and 70 %, respectively, of the total number of
days, while the coverage of the meteorological and pollutant data were
> 80 %.
Evaluation
The overall treatment of the measured DMPS data was performed according to
the procedure protocol recommended by Kulmala et al. (2012). The individual
size distributions were fitted by lognormal functions using the DoFit
algorithm (Hussein et al., 2004). The identification of an NPF and subsequent
particle growth process was accomplished by using the algorithm of Dal Maso
et al. (2005). The growth rate (GR) of particles in the size interval of
6–25 nm was determined by a lognormal distribution function method
(Kulmala et al., 2012). The formation rate (Jd) of particles with a
diameter d and condensation sink (CS) were computed according to Kulmala et
al. (2012) and Dal Maso et al. (2002), respectively. It is worth mentioning
that Jd depends implicitly on GR. The earliest estimated time of the
beginning of nucleation (t1), the latest estimated time of the beginning
of nucleation (t2) and the ending time of the particle growth process
(te) were derived by a comparative method (Németh and Salma, 2014).
The time t1 also includes the time shift that accounts for the particle
growth from the stable neutral cluster mode at 1.5 ± 0.4 nm (Kulmala
et al., 2007) to the smallest detectable diameter limit of the DMPS systems
by adopting the GR value in the size window nearest to it in size space. This
approximation can result in an underestimation of the shift by up to 30 %
because GR tends to increase with an increasing d in this size range
(Kulmala et al., 2012). It is noted that the shifts were mostly smaller than
30–40 min, which seems acceptable with respect to the uncertainty of the
starting time parameter t1 and to the ordinary dynamics of atmospheric
processes. The gas-phase H2SO4 proxy value was derived as
[SO2] × GRad/CS for intensities > 10 W m-2, and the
scaling factor k between the proxy value and H2SO4 concentration
was estimated by an empirical relationship of k=1.4×10-7 × GRad-0.70, where GRad has a unit of W m-2
(Petäjä et al., 2009). Average proxy values were expressed as
absolute concentrations, while the variations in the proxy in figures were
shown without adopting the scaling factor. The scaling factor k was derived
specifically for a remote boreal site, and since urban areas are expected to
differ from remote regions in this respect (Mikkonen et al., 2011), the
diurnal cycling of GRad involved implicitly in the scaling factor could
interfere or distort the relationships and trends shown in the figures.
Retrospective movement of the air masses was assessed by backward
trajectories, which were generated by using the air parcel trajectory model
HYSPLIT v4.9 with an option of vertical velocity mode (Draxler and Rolph,
2013). An embedded Global Data Assimilation System meteorological database was
utilized for the modelling, which yields the calculated results on a
1∘ latitude–longitude grid. Trajectories arriving at the receptor
sites at a height of 200, 500 and 2300 m above the ground level were
calculated. For the NPF event days, the start time of the backward modelling
was set to the ending time of the particle growth (te), and the end time
of the computer run was fixed at the earliest beginning of the nucleation
(t1). For the non-event days, the end and start times of the modelling
were set to 13:00 and 01:00 UTC + 1, respectively.
A correlation analysis between the joint 2-year-long data sets for Budapest
and the K-puszta station was performed on a daily basis. The index of occurrence
of 1 was assigned to NPF event days, 0 to undefined and missing days, and
-1 to non-event days. The Pearson correlation coefficient and its transformed
t value was calculated as
t=rn-21-r2
for n=731 items and assuming Student's t distribution with n-2 degree of freedom.
Wind speed data measured at a height of 10 m above the ground were
recalculated to a height of 200 m by using the power law approach with an
exponent of 0.2 (Irwin, 1967). These WS data were averaged for the area
between Budapest and the K-puszta station considering different time intervals.
The following four cases were considered: NPF events identified at both
measurement sites (BpY&KpY); an event in Budapest and no event at the
K-puszta station (BpY&KpN); no event in Budapest and an event at the K-puszta
station (BpN&KpY); and no event in either the Budapest or K-puszta station
(BpN&KpN). For the case BpY&KpY, the WS data for the site with the
earlier NPF event were selected from the time t1-1 h of the earlier
site to the time t1 of the site with the delayed NPF event, while the WS
data for the site with the delayed event were selected from the time t1
of the earlier site to the time t1+1 h of the delayed site. Finally,
the two selected data sets were averaged to a synoptic WS value. For the
cases BpY&KpN and BpN&KpY, the mean WS value was obtained by averaging
the two WS data sets between the times t1 and te. For the case
BpN&KpN, the mean WS value was derived by averaging jointly both WS data
sets from the mean time t1 to the mean time te. These selections
represent sensible and representative approximations to reality. As the next
step, comparison of the delay time with the travel time of the synoptic wind
was expressed by
Distribution of monthly mean NPF frequency in Budapest
and at the K-puszta station. Annual mean frequencies are indicated by horizontal
lines and figures. The spring and autumn maxima are highlighted in yellow
bands.
τ=Δt1DWS,
where D=71 km is the distance between the centre of Budapest and the K-puszta
station. If the ratio τ→1, the nucleating air mass may have
transported by advection from the upwind site to the downwind site. If τ is substantially smaller than 1, the NPF event at the downwind site could
not have been transferred by advection from the upwind site but rather formed
somewhere else. In our data, τ>1 was caused by large
(> 7 m s-1) WSs, and this took place in a very limited number case,
so further investigations (e.g. on the origin of these air masses) require
longer data sets.
Results and discussion
Similarities in NPF occurrence
The annual mean frequencies of NPF events were substantial at our measurement
sites compared with most other sites reported in scientific literature
(Table 1; Kulmala et al., 2004, and references therein; Dal Maso et al.,
2005; Manninen et al., 2010; Borsós et al., 2012; Dall'Osto et al.,
2013). This indicates that the typical meteorological and chemical conditions
(e.g. higher annual mean T inside the basin, presence of forested areas
and availability of SO2 precursor) within the Carpathian Basin favour
the occurrence of NPF. The seasonal variability of the NPF frequency was very
similar at both sites with a minimum in winter and two local maxima, one in
spring and the other in autumn (Fig. 2). The spring maximum took place in
April during the first year and in March during the second year. Such a shift
can be caused by interannual differences in meteorological conditions (Dal
Maso et al., 2005; Hamed et al., 2010) or biogenic cycling through emissions
of volatile organic compounds (VOCs) from vegetation (Riipinen et al., 2011;
Riccobono et al., 2014). The two measurement sites respond identically to
these influences.
Number of days with obvious NPF event, unambiguously no NPF event,
undefined days and missing days in Budapest and at the K-puszta station for two
1-year-long time intervals in 2008–2009 and 2012–2013.
Time interval/class
Budapest
K-puszta
2008–2009 (365 days)
Events
83
100
Non-events
229
146
Undefined
34
78
Missing
19
41
2012–2013 (366 days)
Events
96
125
Non-events
231
180
Undefined
19
40
Missing
20
21
Number and relative frequency of air mass trajectories
arriving at the Budapest and K-puszta station in a parallel direction from NW and
SE, in perpendicular directions, and in unclassified (other) directions
relative to the Budapest–K-puszta station geographical connecting line when there were NPF events identified at both sites
(BpY&KpY), an event in Budapest and no event at the K-puszta station
(BpY&KpN), no event in Budapest and an event at the K-puszta station
(BpN&KpY), and no event at either of the sites (BpN&KpN).
Trajectory
BpY&KpY
BpY&KpN
BpN&KpY
BpN&KpN
direction
No.
%
No.
%
No.
%
No.
%
Parallel from NW
23
36
5
33
9
16
91
34
Parallel from SE
20
31
2
13
28
48
39
14
Perpendicular
16
25
8
54
21
36
136
50
Other
5
8
0
0.0
0
0.0
4
2
All
64
100
15
100
58
100
270
100
In order to investigate more thoroughly whether and how the occurrence of NPF
was connected between the two measurement sites, and over the whole basin, we
made a statistical analysis and investigated air mass transport effects. For
the occurrence of NPF, the joint 2-year-long data set resulted in a
correlation coefficient of 0.429, with a Student's t value of 12.829. The
critical Student's t value at a statistical confidence level of 99.99 %
is 3.912, which means that there was a significant linear relationship in the
occurrence of the NPF between the two sites. In most cases, the particle
growth associated with NPF (the presence of a banana-shaped curve) could be
traced for 8–13 h, during which time the air parcel containing nucleated
particles travelled a distance comparable to the dimensions of the basin.
This result is consistent with other modelling studies on the spatial extent
of NPF (Crippa and Pryor, 2013; Németh and Salma, 2014; Pietikäinen
et al., 2014).
Incidence of NPF events
The geographical straight line between the two measurement locations is
identical with the prevailing wind direction (NW) in the area, which makes it
possible to compare the exact timing of the NPF processes at these sites to
the air mass advection between the sites (Table 2). Air mass backward
trajectories derived for all days were grouped into the following cases:
trajectories that ran parallel to the geographical connecting line and arrived from the NW, trajectories parallel to the connecting line and arriving from the SE,
trajectories in largely perpendicular directions to the connecting line, and
trajectories in unclassified directions. Days with quantifiable NPF event and
non-event days in the 2-year-long data set were considered in this
evaluation. For simultaneous event days (BpY&KpY), the NPF events in
Budapest occurred later than at the K-puszta station in 75 % of the relevant
days, with a mean delay time of 1 h 54 min. There were 4 days when the
NPF events in Budapest happened earlier than at the K-puszta station, but their
mean delay time involved a relative uncertainty of > 80 %. For the
parallel direction from SE, the NPF events in Budapest occurred later than at the K-puszta station in 85 % of the relevant days with a mean delay time of
1 h 11 min. The opposite timing (on 3 days only) yielded a mean delay
time with a rather high uncertainty. For the parallel direction from NW, the
NPF events in Budapest occurred later than at the K-puszta station on 33 % of
the relevant days, with a mean delay time of 1 h. During the days when NPF was taking place at both
sites (about 10 % of the days), the mean and standard deviation of the
ratio τ (Eq. 2) were 0.34 ± 0.25. This indicates that the air
masses only reached approximately one third of the geographical distance when
the NPF had already started at the downwind site. Hence, the NPF observed at
the downwind site was not because of air mass advection from the upwind site but rather took place simultaneously over large distances in the basin. At
the present level of our knowledge, advection of nucleating air masses cannot
be excluded in a few cases.
The cumulative results outlined in Sects. 3.1 and 3.2 show that the NPF
events observed in the city and its rural background appear in a consistent
and spatially coherent way. We interpret this as the result of a common
atmospheric nucleation phenomenon in the region with some urban influence.
Site-to-site differences in NPF properties
There were, however, clear differences in the NPF process between the city
and rural background. The annual mean NPF occurrence frequencies of 24
and 28 % at the Budapest sites were smaller by factors of 1.3 and 1.4,
respectively, than at the K-puszta station (Fig. 2). Moreover, a continuous suppressing tendency from the rural background through the near-city
background to the city centre was found. The mean values of J6 and GR
for central Budapest exceeded that for the K-puszta station by a factor of 2
and 1.6, respectively, when considering the whole measurement data set
(Table 3). This is consistent with the idea that particles capable of
escaping coagulation scavenging grow faster in polluted air compared to
cleaner environments. Large values of GR are typical for polluted urban
atmospheres, such as New Delhi (GR = 11.6–167 nm h-1; Kulmala et
al., 2005), Mexico City (15–40 nm h-1; Iida et al., 2008), South
Africa (3–21 nm h-1; Laakso et al., 2008) or Shanghai (11.4 ± 9.7 nm h-1; Xiao et al., 2015). Quantifiable-NPF events
at the K-puszta station started from 05:35 (on 28 April 2009) to 12:46 (on
15 June 2009). The starting times in the near-city background and city centre
of Budapest ranged from 06:55 (on 25 August 2012) to 12:24 (on
11 October 2012) and from 06:11 (on 28 April 2009) to 11:43 (on 9 May 2009),
respectively.
Mean J6, GR and starting time parameter t1 with
standard deviations for quantifiable regional NPF events in Budapest and at the K-puszta station separately for two 1-year-long time intervals in 2008–2009
and 2012–2013. Numbers of days with quantifiable NPF events are also shown.
The measurements in Budapest were performed in the city centre in
2008–2009, while they were carried out in the near-city background in
2012–2013.
Time interval/property
Budapest
K-puszta
2008–2009 (365 days)
No. of quantifiable events
31
45
J6 (cm-3 s-1)
4.2 ± 2.5
1.9 ± 1.5
GR (nm h-1)
7.7 ± 2.4
4.8 ± 2.3
t1 (hh:mm, UTC+1)
09:25 ± 01:11
08:48 ± 01:33
2012–2013 (366 days)
No. of quantifiable events
43
55
J6 (cm-3 s-1)
2.1 ± 1.5
1.8 ± 1.4
GR (nm h-1)
5.1 ± 1.5
4.2 ± 2.1
t1 (hh:mm, UTC + 1)
08:44 ± 01:10
08:31 ± 01:27
Medians of gas-phase H2SO4 concentration,
condensation sink (CS), SO2 concentration, global radiation (GRad),
relative humidity (RH), air temperature (T), wind speed (WS), cloudiness
(n), planetary boundary layer (PBL) height, O3 concentrations on the
actual day and previous day, aerosol particle number concentration in the
diameter range from 10 to 100 nm (N10-100), and PM10 mass
concentration for the time interval when NPF events were identified in both
Budapest and at the K-puszta station (BpY&KpY) and when there was an event in Budapest and no event
at the K-puszta station (BpY&KpN), no event in Budapest and an event at the K-puszta station (BpN&KpY), and no event in both Budapest and at the K-puszta station
(BpN&KpN).
Variable
BpY&KpY
BpY&KpN
BpN&KpY
BpN&KpN
Budapest
K-puszta
Budapest
K-puszta
Budapest
K-puszta
Budapest
K-puszta
[H2SO4] × 10-6 (molecules cm-3)
5.1
5.4
4.4
4.3
3.4
4.0
3.3
3.5
CS × 103 (s-1)
7.9
6.6
8.8
6.8
14.6
8.1
11.9
9.6
SO2 (µg m-3)
7.1
6.2
6.9
5.3
7.6
6.9
7.2
6.1
GRad (W m-2)
310
276
338
346
225
240
113
122
RH (%)
40
45
41
44
54
61
70
78
T (∘C)
18.2
17.4
22
24
16.0
15.6
7.7
8.0
WS (m s-1)
2.6
3.5
2.2
2.9
2.2
3.7
2.1
3.0
n (okta)
2.6
2.5
4.4
4.8
5.6
5.3
6.4
6.3
PBL (km)
0.96
0.95
1.31
1.31
0.78
0.81
0.57
0.53
O3 (µg m-3)
76
83
93
96
61
75
46
52
O3 for prev. day (µg m-3)
n.r.
76
n.r.
62
n.r.
75
n.r.
49
N10-100 × 10-3 (cm-3)
8.5
8.3
8.2
2.6
6.5
7.3
4.1
2.6
PM10 mass (µg m-3)
21
21
20
16.9
26
22
28
23
n.r.: not relevant
The relationship between the major source and sink for gas-phase
H2SO4 for the event days and non-event days is shown in Fig. 3
separately for Budapest and K-puszta. The data for nucleation days are means
averaged from the time t1 to time t2 of an NPF event. The data for
non-event days are means derived by averaging between the overall mean times
t1 and t2. All time data were expressed in UTC + 1.
Figure 3 suggests that the CS effectively suppresses NPF at values larger
than about 20 × 10-3 s-1 at both sites. The common
limiting CS value is likely related to some environmental features in the
Carpathian Basin. At smaller CS values, a large number of non-event days
is located above the dividing line in Fig. 3, which can be explained by
factors other than CS being active in suppressing the NPF. These include high
concentrations of inhibiting chemical species (Kiendler-Scharr et al., 2009),
low concentrations of stabilizing compounds such as oxidized VOCs (Riccobono
et al., 2014), NH3 and amines (Almeida et al., 2013), or large RH (Hamed
et al., 2011). The much lower fraction of event days located below the same
dividing line supports the principal role of H2SO4 in the NPF
process (Sipilä et al., 2010), especially for Budapest. The median values
of the H2SO4 proxy concentration for the event days in Budapest
(4.8 × 106 molecules cm-3) and K-puszta
(4.7 × 106 molecules cm-3) were larger by factors of 1.4
and 1.2, respectively, than for the non-event days at these two sites
(Table 4). The mean diurnal variation of the H2SO4 proxy was also
very different between the event and non-event days, as well as between the
two sites (Fig. 4). At the mean NPF starting time for Budapest of
t1 = 09:25 UTC + 1, the H2SO4 proxy appears to be
separated into larger values
(> 45 × 104 µg m-5 W s ∝ 6 × 106 molecules cm-3) for event days and smaller
values (< 25 × 104 µg m-5 W s ∝ 3×106 molecules cm-3) for non-event days. This
partitioning is related to the availability of H2SO4 and seems to
explain the observed variability in the occurrence of NPF in Budapest. In
contrast, the H2SO4 proxy for the K-puszta station at the mean NPF
starting time of t1 = 08:40 UTC + 1 lies in a narrow band,
except for the case BpY&KpY. The H2SO4 proxy utilized in the
present study only takes the main atmospheric oxidation of
SO2 by the OH radical into account. Recent field observations supported by laboratory
experiments and theoretical considerations point to capacities of stabilized
Criegee intermediates (sCIs) in forests to oxidize SO2 into
H2SO4, with a contribution of up to 33–46 % of H2SO4
concentration at ground level (Mauldin III et al., 2012; Boy et al., 2013).
SCIs are formed by ozonolysis of unsaturated organics, including
terpenoid compounds which are emitted in large amounts by plants. Thus, a
biogenically related mechanism cannot be excluded for the NPF events observed
just after the sunrise at the K-puszta station.
Relationship of the major source and sink of gas-phase
H2SO4. The data are shown separately for the quantifiable-event
days and non-event days in Budapest and at the K-puszta station for the whole
2-year-long time interval. Product P of SO2 concentration and global
radiation was considered as the major source and CS as the major sink. The
yellow areas indicate the CS range in which the NPF events were suppressed
over the whole region.
Hourly mean values of gas-phase H2SO4 proxy in
Budapest and at the K-puszta station averaged for the days when NPF events were
identified in both Budapest and at the K-puszta station (BpY&KpY) and when there was an event in
Budapest and no event at the K-puszta station (BpY&KpN), no event in Budapest
and an event at the K-puszta station (BpN&KpY), and no event in both Budapest
and at the K-puszta station (BpN&KpN). The proxy values at the mean starting
time t1 of the NPF are indicated by dots on the curves.
Surface plot (upper panel) for Sunday, 30 September 2012, showing an NPF and growth event with double consecutive start in the
near-city background of Budapest. Time series of the fitted particle number
median diameter for the nucleation mode are indicated by black dots. For the
onsets 1 and 2, the J6s were 1.34 and 5.9 cm-3 s-1,
respectively, the GRs were 7.7 and 12.9 nm h-1, respectively, and the
starting times t1 were 09:53 and 12:18 current local time (UTC + 2),
respectively. Temporal evolution of particle number concentrations
N6-25, N6-100 and N100-1000 and of RH are displayed in the
middle panel. The lower panel shows the diurnal variation of SO2
concentration, GRad, CS and gas-phase H2SO4 proxy.
Based on the H2SO4 proxy concentration, the mean contribution of
H2SO4 condensation to the particle GR was estimated to be 12.3 and
11.8 % for Budapest and K-puszta, respectively. This indicates that other
chemical species, presumably organic compounds, have a large influence on the
growth of newly formed particles in the basin and possibly also on the NPF
process itself. The increase in the GR with an increasing particle size
reported earlier for the K-puszta station (Yli-Juuti et al., 2009) is
strongly in line with this view. Previous studies have identified extremely
low-volatility organic compounds (ELVOCs) playing an important role in both the
NPF and particle growth. Such compounds were first predicted by Kulmala et
al. (1998) and later identified from the oxidation of α-pinene and
other terpenoids in smog chamber experiments (Ehn et al., 2014; Jokinen et
al., 2015). ELVOCs appear to be formed with substantial mass yields under
atmospherically relevant conditions and their dimers seem large enough to act
as nano-condensation nuclei for their further irreversible growth (Ehn et
al., 2014). Our results indicate a clear contribution of compounds other than
H2SO4 in the initial and subsequent growth processes. Since the
saturation vapour pressure of those compounds needs to be very low, it is
probable that ELVOCs are the main contributors for this in the Carpathian
Basin.
Spatial variability of NPF occurrence on a subregional scale
In order to find out the primary causes for the subregional differences, we
derived median values of the relevant meteorological data and air pollutant
concentrations separately for the following cases: BpY&KpY, BpY&KpN,
BpN&KpY and BpN&KpN (Table 4). Since the details of the possible
oxidation of SO2 by sCIs are not exactly known, median O3
concentrations for the day before an NPF event were also added for the
K-puszta station. The averaging was first performed from time t1 to time
te. In the case of BpY&KpY, the actual time parameters for each
measurement site were utilized. In the cases of BpY&KpN and BpN&KpY,
the time parameters of the NPF event for one of the measurement sites were
used for the other, non-event site as well. In the case of BpN&KpN, the
overall-mean time parameters t1 and te were adopted as averaging
limits. For GRad and H2SO4 concentration, the ending time te
was replaced by time t2. These averaging limits represent time intervals
in which the NPF event and particle growth are the most pronounced. Finally,
the mean values for particular days were further averaged separately for the
four combination cases mentioned above. It is worth mentioning that an NPF
occurrence depends on a complex set of multiple variables. All of them
contain relevant information, while it cannot be expected that any standalone
property or paired relationship can explain, or even be directly linked to,
the NPF occurrence.
The variability in GRad, RH, T and PBL height are strongly biased by the
seasonal cycle of solar radiation via the distribution of the monthly NPF
frequency, and, therefore, their tendencies are to be approached with special care. The variables PM10 and WS did not seem to contribute
substantially to the explanation of the heterogeneity, while N10-100
just reflected the fact that NPF increases the number concentration of pre-existing
particles extensively (by a factor of 2–3 for Budapest; Salma et al., 2011).
Mean concentrations of O3 were larger at the K-puszta station than in
Budapest, and they were also larger on NPF days than on non-event days,
which indicates a larger photochemical activity in the former case.
Cloudiness showed a weak reciprocal tendency with NPF. The occurrence of
NPF events did not seem to be sensitive to the SO2 concentration, which
suggests that this precursor gas was available at sufficient quantities for
NPF to occur during most of the time. The excess concentrations are realized
in spite of the fact that the estimated reduction in SO2 emission
between 1990 and 2004 was more than 60 % that in most European countries,
including Hungary (Hamed et al., 2010). The condensation sink in Budapest
exhibited a general dependency in that NPF events occur preferably on days with
low values of CS values, being larger by approximately 50 % during the
non-event days compared with the event days. This implies that the CS
affected the NPF in the Budapest area and that it can have a preventative
influence on the events. In contrast, the mean CS values for K-puszta station
showed much less or even little effect. The condensation sink depends
sensitively on the concentration and size distribution of pre-existing
aerosol particles. At the K-puszta station, the average particle number
concentration levels are substantially lower, and, thus, the CS values and
their changes are smaller as well.
For the mixed cases of BpN&KpY and BpY&KpN, the difference between the
two types of data was considered to be significant if they diverged at least by a
factor of 2. For cloudiness, a difference larger than 2 okta at an absolute
value larger than 5 okta was required, similarly to RH, for which a
difference of 15 % at an absolute values of > 70 % was needed for
a significant difference (Boy and Kulmala, 2002). These criteria are in line
with the current understanding of the conditions for the NPF process (Hamed et
al., 2011) and represent sensible approximations to reality. Of 58 cases of
BpN&KpY, on 19 days the CS was significantly larger, on 8 days the
H2SO4 proxy was significantly smaller, on 8 days the CS was
significantly larger and the proxy was significantly smaller, on 4 days both the absolute
value of the RH and its difference between the two sites were large, on 3 days
both the absolute value of the cloudiness and its difference between the two sites were large, and on 1 day the proxy was significantly
smaller and both the absolute value of the cloudiness and its difference between the two sites were large in Budapest
compared with the K-puszta station. These findings explain 77 % of the
investigated days. On a further 2 days, some important data were missing,
and, therefore, their evaluation was not possible. In 23 % of the relevant
days, we could not prove that there are plausible causes for the spatial difference. About
15 % of these days occurred in summer, late spring or early autumn,
when the O3 production and its chemical reactions could be important,
and there was an indication of increased O3 concentration overnight
before the NPFs. It is hypothesized that most of these unexplained events at the K-puszta station were explicit cases of an sCI oxidation mechanism. For the
case BpY&KpN, 11 days (67 % of the days) could be explained by
greater cloudiness, RH, CS and WS and/or lower SO2 at the K-puszta
station compared with Budapest. The number of days with missing data was
three. Possible factors for the unexplained days can also include different
weather systems at, or weather fronts between, the measurement sites,
different air masses, or the conservative selection criteria applied. The area
between Budapest and the K-puszta station is inhabited, and the effects of
settlements on the atmospheric environment also limit the homogeneity of
larger air masses. By analysing the data set, we can conclude that the two
major candidates for explaining the differences in the occurrence of NPF are
the higher CS in Budapest and the smaller gas-phase H2SO4 concentration
at K-puszta.
Regional- and urban-type NPF events
We observed NPF and subsequent particle growth events with at least two
consecutive onsets on some days, in particular in the near-city background. Of the 43 quantifiable
events there, there were 8 NPF events with a double start. A surface plot displaying a typical double start together with
the temporal evolution of some related quantities is shown in Fig. 5 as an
example. The quantities related to the NPF events (e.g. N6-25 and
gas-phase H2SO4 proxy) varied substantially and rapidly in time,
whereas the concentration N100-1000, which represents a larger region,
stayed stable. This means that there was no extraordinary change in the
dynamics of the PBL or weather situation during the time interval of the two
onsets. In addition, there was no indication of sudden changes in the local
WD, WS and GRad data or in the air mass origin and path during the relevant
time intervals. Based on these arguments, an interrupted and renewed (started
over) NPF and particle growth process due to the changes in local
meteorology or to two different air masses transported to the measurement
site can largely be excluded, and there must be other primary reasons for the
double starts.
Dynamic properties for the NPF with single start and for
the onsets 1 and 2 of the events with double start in the near-city
background of Budapest. The data pairs corresponding to the two onsets of an
event are indicated by numbers. The data point marked as possible double
onset (on 28 April 2012) was assigned to a weak onset 1 and a rather
intensive onset 2 by visual inspection although the identification of the
two nucleation modes in the size distributions by fitting was not achieved,
likely due to the fluctuating data.
The characteristics of NPF for the event consisting of two onsets were quite
different from each other (Table 5). The mean ratio and standard deviation of
J6 and GR between the two onsets were 2.5 ± 1.0 and
1.8 ± 0.5, respectively, and the mean difference and standard deviation
between the corresponding starting times were 2 h 12 ± 36 min. The
individual J6s and GRs for the NPF events with a single start and for the two onsets of the NPF events with a double start are shown in
Fig. 6. The dynamic properties of the onset 2 (later event) were always
larger than those of the corresponding onset 1 (earlier event). In addition,
the mean NPF characteristics of the earlier onsets were similar to those of
the single-onset events within the uncertainty interval, indicative of their
common cause, and also similar to those of the rural background data
(Yli-Juuti et al., 2009). At the same time, the mean NPF characteristics of
the later onsets were close to those for the city centre data (Salma et al.,
2011). This suggests that the later events occurred in a more polluted air,
which was unambiguously of urban origin.
Range of J6, GR and starting time t1 in UTC + 1
together with their mean values and standard deviations (SDs) calculated
jointly for the single events and the onset 1 of the NPF events with double
start (regional events) and separately for the onset 2 of the events with
double start (urban events) in the near-city background of Budapest.
Property
J6 (cm-3 s-1)
GR (nm h-1)
t1 (hh:mm)
Single + onset 1 (43 days)
Range
0.35–8.8
3.0–10.7
06:07–12:07
Mean ± SD
2.1 ± 1.5
5.1 ± 1.5
08:44 ± 01:10
Onset 2 (8 days)
Range
0.96–5.9
8.1–12.9
09:05–12:18
Mean ± SD
3.7 ± 1.6
10.1 ± 1.7
10:27 ± 01:05
The interpretation given above is supported by the observations that the
later onsets generally happened when the H2SO4 proxy was high, and
they might also be associated with larger Js, GRs and, more importantly,
with larger GRs normalized to the H2SO4 proxy (Fig. 7). These
relationships appear as tendencies, which suggests that the differences
between the two onsets are of qualitative character. At the K-puszta station,
there was no NPF observed on 2 of the 8 related days, and for 1 day,
some important data were missing, and, therefore, the number of available
data points for the K-puszta station is limited. It appears, however, that the
overall conditions for the NPF process are met for the whole region. If this
is realized, then a regional event likely occurs, which can be accompanied by
an urban-type NPF at a later time. This may take place, for instance, by
mixing regional and urban air parcels that exhibit different properties,
which are mainly governed by local PBL dynamics and urban heat island effects.
We relate these distinctions to an urban influence. Our interpretation is
supported by a previous observation of NPF event with multiple onsets in
semi-clean savannah and industrial environments (Hirsikko et al., 2013), in
addition to which it fits very well into the existing ideas on mixing
regional and urban air parcels that exhibit different properties such as
precursor concentrations, T and RH, and it is mainly governed by local
PBL dynamics (Nilsson and Kulmala, 1998).
Dependence of the growth rate of NPF for a unity
H2SO4 proxy on the proxy value separately for the onsets 1 and 2
of the events with double start in the near-city background of Budapest and
for the regional NPF at the K-puszta station on identical days. The numbers next
to the symbols express J6 in a unit of cm-3 s-1.