Introduction
Research assessing the atmospheric deposition of nitrogen (with a focus on
inorganic N in rainwater i.e., ammonium and nitrate) can be traced back to the
mid-1800s (Miller, 1905, and references therein) as it was accepted to be a
vital plant nutrient. Miller (1905) mentioned organic nitrogen in rain
samples as well. To quote Miller, “With regard to the amount of organic
nitrogen in the rainwater, the only available analyses relating to Rothamsted
are those of Frankland who found from 0.03 to 0.66 per million in
69 samples”. Cornell et al. (1995) highlighted the importance of organic
nitrogen in rain and snow accounting for almost half of the total atmospheric
dissolved nitrogen deposition. Since then, research defining the quantitative
importance of soluble organic nitrogen in the atmospheric transport of
nitrogen has greatly expanded (Neff et al., 2002; Cornell et al., 2003; Mace
et al., 2003a, b, c; Glibert et al., 2005; Sorooshian et al., 2008; Violaki
and Mihalopoulos, 2010; Violaki et al., 2010; Altieri et al., 2016).
Water-soluble organic nitrogen (WSON) arises from a variety of sources including both natural and
anthropogenic. Anthropogenic sources include agricultural activities
(including fertilizer application, livestock and animal husbandry), cooking,
high-temperature fossil fuel combustion, vehicle exhaust, man-made biomass
burning and industrial activities. In contrast, natural sources of WSON
include mineral dust, bacteria, algal blooms, degraded proteins, sea salt,
organic debris and natural biomass burning (Neff et al., 2002; Cornell et al.,
2003; Mace et al., 2003a, b, c; Glibert et al., 2005; Sorooshian et al.,
2008; Cape et al., 2011; Altieri et al., 2016). Atmospheric organic nitrogen
can also be formed through chemical reactions. For example, reactions between
volatile organic compounds, NOx and ammonium sulfate aerosols may lead
to the formation of nitrogen-containing compounds (Surratt et al., 2008;
Galloway et al., 2009; De Haan et al., 2011; Yu et al., 2011). Furthermore,
atmospheric organic nitrogen plays an essential role in many global processes
which may impact the chemistry of the atmosphere as well as climate and
biogeochemical cycles. Similar to ammonium, some organic nitrogen species
such as urea and amines have acid-neutralizing capacities (Ge et al., 2011).
It has been shown that nitrogen-containing organic compounds nucleate cloud
droplets and may contribute considerably to the indirect aerosol effect
(Twohy et al., 2005). Phytoplankton and bacteria production in aquatic
environments has been found to be stimulated by the addition of water-soluble
organic nitrogen (Timperley et al., 1985; Peierls and Paerl, 1997; Seitzinger
and Sanders, 1999). The laboratory experiments performed by Seitzinger and
Sanders (1999) demonstrated the production of coastal marine bacteria and
phytoplankton, which are stimulated by the addition of water-soluble organic
nitrogen, 45–75 % being bioavailable. From the mid-1800s to 2000, as a
result of anthropogenic activities, reactive nitrogen and reactive
anthropogenic organic nitrogen increased by almost 3- and 5-fold,
respectively, leading to a significantly modified global nitrogen cycle
(Jickells et al., 2017). This in turn has impacted marine nitrogen
biogeochemical cycling (Galloway and Cowling, 2002; Galloway et al., 2008; Duce et al., 2008;
Jickells et al., 2017).
The Mediterranean Sea is characterized by oligotrophic surface waters with
low-nutrient, low-chlorophyll (LNLC) regions. This has been attributed to
mainly anti-estuarine (reverse thermohaline) circulation (Hamad et al.,
2005). The eastern Mediterranean (25) has higher molar N / P ratios than
those observed in the western Mediterranean (22) and the Redfield ratio (Krom
et al., 2004; Yılmaz and Tuğrul, 1998). Generally, the primary
productivity in the eastern Mediterranean is phosphorus-limited (Krom et
al., 1991, 2010; Powley et al., 2017). Depending on the season,
limitation by nitrogen or co-limitation by nitrogen and phosphorus in the
eastern Mediterranean has been reported (Yücel, 2013, 2017, and
references therein). Based on molar N / P ratios in the atmospheric input
(order of magnitude higher than that of Redfield; Markaki et al., 2003, 2010;
Koçak et al., 2010) and riverine fluxes (at least 1.8 times larger than
that of Redfield; Ludwig et al., 2009; Koçak et al., 2010) it has been
suggested that the eastern Mediterranean receives excessive amounts of
dissolved inorganic nitrogen and that this unbalanced input may result in even
more phosphorus deficiency (Ludwig et al., 2009; Koçak et al., 2010),
whilst the atmospheric deposition of reactive nitrogen may cause accumulation
of nitrogen in the water column (Jickells et al., 2017). Very little research has
focused on the importance of water-soluble organic nitrogen input to marine
productivity in the eastern Mediterranean (Mace et al., 2003a; Violaki and
Mihalopoulos, 2010; Violaki et al., 2010). Hence, the unique contributions of
the current study will be to (i) define the temporal variability of
atmospheric water-soluble organic nitrogen, (ii) assign the origin of the
water-soluble organic nitrogen, (iii) assess the influence of mineral dust on
water-soluble organic nitrogen and (iv) enhance our knowledge of the
quantitative dry and wet deposition of water-soluble organic nitrogen and
its possible influence on marine productivity in the northeastern Mediterranean.
These aims will be achieved by using the acquired data from the analyses for
water-soluble inorganic and organic nitrogen species of a series of size-fractionated aerosol (coarse and fine) and rain samples collected from
March 2014 to April 2015 from the northern coast (Erdemli, Turkey) of the
Levantine Basin, eastern Mediterranean.
Material and methods
Sampling site description
Aerosol and rain sampling was carried out at a rural site located on the
coast of the eastern Mediterranean, Erdemli, Turkey
(36∘33′54′′ N, 34∘15′18′′ E). The sampling tower
(above sea level ∼ 22 m, ∼ 10 m away from the sea) is situated
at the Institute of Marine Sciences, Middle East Technical University
(IMS-METU). Its immediate vicinity is surrounded by cultivated land to the
north and to the south of the northern Levantine Basin. Although the site is
not under the direct influence of any industrial activities (such as soda production and
fertilizer production), the city of Mersin with a population of around 800 000 is
located 45 km to the east of the sampling site (Kubilay and Saydam, 1995;
Koçak et al., 2012), and hence aerosol and rainwater samples may have been
influenced by the aforementioned regional anthropogenic activities when air mass
is transported from the east.
Sample collection and preparation
Aerosol. A Gent-type stacked filter unit (SFU) was used to collect
aerosol samples in two size fractions (coarse: d=10–2.5 µm and
fine: d<2.5 µm) (for more details, see Hopke et al., 1997;
Koçak et al., 2007). Briefly, the first section of the filter holder was
loaded with an 8 µm pore size polycarbonate filter (Whatman Track
Etched 111114, circle diameter: 47 mm), whilst the second section was loaded
with a 0.4 µm pore size polycarbonate filter (Whatman Track
Etched 111107, circle diameter: 47 mm). The cassette unit was then placed
into the cylindrical cassette holder, which is designed to prevent the
intrusion of particles larger than 10 µm when the sampler is
operated at a flow rate of 16.0–16.5 L min-1. Daily (24 h) temporal
sample resolution was carried out. Operational blank filters were processed
in the same way as the collected samples with the exception that no air was
passed through the filters. In order to minimize any possible contamination,
the filter loading and unloading were achieved in a laminar airflow cabinet.
The aerosol sampling campaign commenced in March 2014 and ended in
April 2015. During the sampling period, a total of 674 aerosol samples in two
size fractions (coarse = 337; fine = 337) were obtained. The
observational coverage of the aerosol sampling period was 80 %. The
observational coverage for winter, spring, summer and fall was respectively
60, 92, 81 and 79 %. The seasonal observational coverage, after applying
a precision value of 0.3 (for more details, see Sect. 2.4 and Eq. 4), was
found to be comparable for winter (49 %), spring (53 %), summer
(51 %) and fall (52 %). The sampling was terminated from time to time
due to technical malfunction of the SFU and/or the cleaning procedure of the
sampling apparatus.
Rain. Rainwater samples were collected using an automatic wet/dry
sampler (Model ARS 1000, MTX Italy). A total of 23 rain samples was
collected during the sampling period. After each rain event, the rainwater
samples were immediately transferred to the laboratory for filtration
(0.4 µm Whatman, polycarbonate filters). Operational blanks for
rain samples were taken by using 100 mL of Milli-Q water after cleaning the
HDPE buckets with phosphate-free detergent, HCl (10 %) and Milli-Q water
(3 times).
Storage of samples. Aerosol and rainwater samples were stored frozen
(-20 ∘C) immediately after collection until analyses (not more
than a month). Cape et al. (2001) showed that there were no
significant losses for inorganic and organic nitrogen during storage
(freezing for 3 months) of rain samples with an added biocide.
Sample preparation. In order to determine the concentrations of
water-soluble total nitrogen species (WSTN, NO3- and NH4+) and
major water-soluble ions (Cl-, SO42-, Na+, K+,
Mg2+, Ca2+) in an aerosol sample, one-quarter of the filter was
extracted for 60 min in 20 mL ultra-pure water (18.2 Ωm) by
mechanic shaking. About 100 µL chloroform (Merc 2444, 99.8 %)
was added as a preservative to prevent biological activity after removing the
filter (Bardouki et al., 2003; Koçak et al., 2007). Before measuring the
water-soluble species, extracts were filtered with 0.4 µm pore size
polycarbonate filters.
Chemical analysis
Water-soluble total nitrogen. High-temperature catalytic oxidation
(Torch Teledyne Tekmar TOC/TN) was applied to determine the WSTN
concentrations in the aerosol and rainwater samples. The liquid aliquot of
the sample is injected into the combustion furnace (750 ∘C) and the
N in the sample was then converted to NO gas. The carrier gas (high-purity
dry air) sweeps the sample into the nondispersive infrared detector. From here,
the sample is carried to the nitrogen module. In this unit NO is mixed with
O3 since the chemiluminescent detection of NO is based on the reaction
between NO and O3. After the formation of excited nitrogen dioxide
(NO2∗), the extra energy is given off as light when NO2∗ relaxes to its ground state. The light signal to an electronic signal for
quantification is then measured by a chemiluminescence detector with a
photomultiplier tube.
The standards were prepared from KNO3 of high purity (> 99 %,
Merck Extra Pure, CC551961). In order to evaluate accuracy of the WSTN
measurements, nitrate, ammonium, urea and mixture of these species were
detected by a Teledyne Tekmar torch instrument. Recovery for these substances
was better than 92 %. In addition, the accuracy of the total nitrogen
determination by the instrument was verified against intercalibration samples
of the QUASIMEME program (Quality Assurance of Information for Marine
Environmental Monitoring in Europe).
Correspondingly, recoveries for QNU277SW (IMS-METU = 4.67 µM,
Mean = 5.17 µM), QNU278SW (IMS-METU = 10.41 µM,
Mean = 11.30 µM) and QNU279SW
(IMS-METU = 4.67 µM, Mean = 5.17 µM) were 90, 92 and
83 %. Blank values of WSTN for aerosol and rain samples were less than
the limit of detection (3.6 nmol).
Water-soluble inorganic and ancillary species. In addition to
NO3- and NH4+, major water-soluble ions concentrations were
measured by using a Dionex ICS-5000 ion chromatography instrument.
Water-soluble anions (Cl-, SO42-, NO3-) were determined
by applying a AS11-HC separation column, KOH (30 mM) eluent and AERS-500
(4 mm) suppressor whilst water-soluble cations (Na+, K+,
Mg2+, Ca2+) were detected electrochemically by using a CS12-A
separation column, MSA (20 mM) eluent and CSRS-300 (4 mm) suppressor
(Product Manual for Dionex IonPac AS11-HC-4m, IonPac CS12A Manual). The blank
contributions for all water-soluble ions in aerosol samples were found to be
less than 10 % and concentrations were corrected for blanks.
Calculations
WSON concentrations (see Eq. 1) were determined from the difference between
the individual concentrations of WSTN and water-soluble inorganic nitrogen
(WSIN) (see Eq. 2) since there is no direct analytical method to detect the
concentration of water-soluble organic nitrogen. The precision for WSON was
calculated via the formula (see Eq. 3) suggested by Hansell (1993). The
precision (75 nmol N m-3) was found to be almost 3 times higher
(see Eq. 4, R∼0.3) than that of the arithmetic mean of WSON in
aerosols, whilst it (90 µmol N L-1) was estimated to be
approximately 4 times larger than that of the volume weighted mean of WSON in
rain. Such high values are not unusual. For example, if the data presented by
Mace et al. (2003a) had been used, precisions would have been 5 and 8 times
higher than those of the concentrations of WSON in aerosol and rain,
respectively. Table 1 shows the number of negative WSON values and the
positive WSON biases for coarse and fine modes. Correspondingly, about 5
(n=18) and 15 % (n=52) of the values were negative in coarse and fine
particles. The substitution with zero yielded 2 and 14 % positive bias
for the coarse and fine mode; whereas the omission of zero resulted in 8 and
34 % positive bias in coarse and fine WSON mean concentrations.
Consequently, the presentation of the general characteristics of the data
includes all negative concentrations (see Table 1) and the values
presented in Table 1 will be used for calculating dry and wet deposition. It
has been stated that the uncertainty in WSON concentrations results from the
additions of errors such as the oxidation efficiency of the method, the sampling
material, the storage of the samples and the usage of preservatives (Cape et al., 2011).
These authors have particularly pointed out the low precision for samples
with low concentrations of WSON and high levels of WSIN (see Eq. 2).
Although the calculation of precision for WSON is very difficult owing to
the aforementioned errors, Hansell (1993) has proposed the estimation of precision
for WSON exclusively relying on measured WSTN and WSIN concentrations.
Consequently, in order to evaluate the variability in the aerosol WSON and
apply positive matrix factorization (PMF), however, a different approach was adopted. To this end, arbitrary
thresholds have been defined as the ratio between the WSON mean concentration and
the calculated precision (see Eq. 4). Thus, during assessment of the variability
in aerosol WSON and the application of PMF, WSON concentrations with R
values larger than 0.3 will be considered since the arbitrary threshold
simply reduces the uncertainty. A total of 216 aerosol samples was found to
have higher R values than 0.3.
The number of negative WSON values and positive biases in coarse and
fine particles at Erdemli.
Coarse
Fine
Number of samples
337
337
Number of negatives
18
52
SZ1–positive bias (%)
2
14
PZ2–positive bias (%)
8
34
1 and 2 refer to as the substitution with zero and the omission
of zero for arithmetic mean, respectively.
WSON=WSTN-WSINWSIN=NO3-+NH4+SWSON=sWSTN2+sWSIN21/2R=WSONMEANSWSON
The rain volume weighted average concentration (CW) of nitrogen
species can be calculated as follows:
CW=∑i=1nCixQi∑i=1nQi.
The wet and dry atmospheric fluxes of nitrogen species were calculated
according to the procedure explained in Herut et al. (1999, 2002). The wet
atmospheric deposition fluxes (Fw) were calculated from the annual
precipitation (Pannual) and the volume weighted mean concentration
(CW) of the substance of interest.
FW=CW×Pannual
The dry deposition (Fd) is calculated as the product of the
atmospheric mean nutrient concentrations (Cd) and their settling
velocities (Vd), where Fd is given in units of
µmol m-2 yr-1, Cd in units of
µmol m-3 and Vd in units of m yr-1.
Fd=Cd×Vd
The settling velocities (Vd; see Eq. 8) for each water-soluble
nitrogen species were calculated by using an approach adopted by Spokes et
al. (2001). Cc and Cf refer to the relative
contribution of coarse and fine modes, and 2.0 and 0.1 cm s-1 are
deposition velocities proposed by Duce et al. (1991) for coarse and fine
particles, respectively.
Vd=Cc×2.0+Cf×0.1
Air mass back trajectories and airflow classification
Three-day back trajectories of air masses at the four altitude levels (1000, 2000,
3000 and 4000 m) arriving at Erdemli station were computed by using
the HYSPLIT dispersion model (HYbrid Single-Particle Lagrangian Integrated
Trajectory; Draxler and Rolph, 2003). Three-day back trajectories reaching
the altitude of 1000 m were classified into six sectors: (i) Middle East,
(ii) north Africa, (iii) Turkey, (iv) eastern Europe, (v) western Europe and
(vi) the Mediterranean Sea, in order to assess the influence of airflow on WSON
concentration in PM10 (for more details, see Koçak et al., 2012).
Positive matrix factorization (PMF) for source apportionment of
WSON
The receptor modeling tool positive matrix factorization (US
Environmental Protection Agency PMF version 5.0, hereinafter referred to as
“PMF”) was utilized to identify the sources of WSON in PM10 at
Erdemli. PMF has been proven to be a robust tool in characterizing the
sources of aerosol (Paatero and Tapper, 1994; Huang et al., 1999; Lee et al.,
1999; Viana et al., 2008; Koçak et al., 2009; for more details, see
Appendix A). EPA PMF 5.0 software mainly consists of model run and rotational
tools (see EPA/600/R-14/108; US EPA, 2014). Before application of the
software, the user must supply two input files, namely concentration and
uncertainty. The former contains concentrations of the aerosol species whilst
the latter contains the corresponding uncertainty for each variable. Uncertainty was
set to 5 % for each species with the exception of WSON (15 %) since
WSON exclusively exhibited high uncertainty (for more details, see Appendix A).
The base run of PMF was achieved by setting the number of runs and random
starting points (in other words, seeds) to 250 and 50, respectively. Base model
displacement (DISP), bootstrap (BS) and bootstrap displacement (BS-DISP)
methods were sequentially used after the base run. The DISP accesses the
rotational ambiguity. DISP error estimates showed that there were no factor
swaps and significant decrease in Q during DISP, being 0 and 0.00,
respectively. Therefore, DISP results did not reveal rotational ambiguity,
implying the solutions to be robust. Except in one case, results from BS and
BS-DISP (n=50) did not indicate any asymmetry or rotational ambiguity for
five factors. To evaluate the rotational ambiguity, different Fpeak values were
applied, considering changes in dQ to be less than 5 %. Furthermore,
G-shape plots of Fpeak solutions were examined to determine convergence
toward the axis or lower/zero contribution. Thus, an Fpeak value of -0.7 was
used and five factors were identified by using PMF 5.0. BS of Fpeak at -0.7
did not reveal any swaps for five factors. The slope of the estimated WSON
against measured WSON was 10 % less than unity with a correlation
coefficient and intercept of 0.87 and 1.5 (nmol N m-3), respectively.
Results and discussion
General characteristics of the data
In this section the general characteristics of the water-soluble organic
nitrogen (WSON), nitrate (NO3-), ammonium (NH4+) and
water-soluble total nitrogen (WSTN) in aerosol and rain will be discussed.
Aerosol. The statistical summary for WSON, NO3-,
NH4+ and WSTN in PM10 aerosol samples obtained from Erdemli
between March 2014 and April 2015 is presented in Table 2. Median values for
WSON, NO3-, NH4+ and WSTN were, respectively, 10, 20, 40 and
10 % lower than those of arithmetic means. Among the nitrogen species,
WSON exhibited the highest arithmetic mean, followed by ammonium and nitrate
concentrations. The maximum concentration of WSON was estimated
to be 79 nmol N m-3, with a mean value and standard deviation of
23.8 ± 16.3 nmol N m-3. The observed arithmetic was comparable
to that reported by Mace et al. (2003a) for the same site. Approximately
66 % of the WSON was associated with coarse particles; the remaining
fraction (34 %) was present within the fine mode. A number of studies
have reported the relative size distribution of WSON for the eastern Mediterranean marine aerosol (Finokalia; Violaki and Mihalopoulos, 2010) and
aerosol observed at remote marine sites (Hawaii; Cornell et al., 2001;
Tasmania, Mace et al., 2003b). The aerosol WSON at Finokalia (68 %) and
Hawaii was primarily found in the fine mode, whilst WSON in South Pacific
marine aerosol (Tasmania) was mainly associated with the coarse fraction. It
is likely that the WSON at Erdemli (a) is relatively less impacted by
anthropogenic sources and/or (b) is more influenced by mineral dust transport
and resuspension of cultivated soil compared to that observed at Finokalia.
The statistical summary of the WSON, NO3-, NH4+ and
WSTN for aerosol (nmol N m-3) and rain (µmol N L-1)
samples collected at Erdemli from March 2014 to April 2015.
Aerosol (nmol N m-3) number of samples: 337
WSTN
WSON
NO3-
NH4+
Arithmetic mean
63.5
23.8
17.8
21.9
Standard deviation
32.0
16.3
15.2
23.8
Median
57.7
21.4
14.3
14.3
Minimum
9.7
-27.9
0.2
0.5
Maximum
176.5
79.0
88.4
164.4
Coarse / PM10 (%)
51
66
87
4
Relative contribution
37
28
35
to WSTN (%)
Rain (µmol N m-3) number of samples: 23
VWM*
73.5
21.5
23.3
28.7
Minimum
24.3
-2.9
0.2
9.1
Maximum
356.2
257.2
74.6
122.6
Relative contribution
29
32
39
to WSTN (%)
* VWM refers to volume weighted mean.
NO3- and NH4+aerosol concentrations ranged between 0.2–88.4
and 0.5–164.4 nmol N m-3, with mean values (standard deviations) of
17.9 (±15.7) and 23.3 (±24.4) nmol N m-3. As expected,
NO3- was mainly associated with coarse particles, accounting for
87 % of the observed mean value, while NH4+ was dominant in the
fine mode, contributing 96 % to the detected mean concentration. Similar
results have been reported for eastern Mediterranean marine aerosol (Bardouki
et al., 2003; Koçak et al., 2007). The predominance of NO3- in
the coarse mode might be due to gaseous nitric acid or other nitrogen oxides
reacting with alkaline sea salts and mineral dust particles. In contrast, the
occurrence of NH4+ in the fine fraction is mainly as a result of the
reaction between gaseous alkaline ammonia and acidic sulfuric acid
(Mihalopoulos et al., 2007).
WSTN concentrations in aerosols varied between 9.7 and
176.5 nmol N m-3 with an arithmetic mean value of
63.5 ± 32.0 nmol N m-3. The mean WSTN
concentration was almost equally influenced by coarse (51 %) and fine
particles (49 %). Table 2 demonstrates the relative contributions of
WSON, NO3- and NH4+ to the WSTN in PM10. As can be
deduced from the table, the WSTN concentration was equally influenced by WSON
and NH4+, each species contributing 37 and 35 %, respectively. In
contrast the contribution of NO3- to WSTN was found to be 28 %.
Rain. Volume weighted mean (VWM) concentrations of WSON,
NO3-, NH4+ and WSTN in rainwater are presented in Table 2,
along with the minimum and maximum concentrations as well as the relative
contributions of WSON, NO3- and NH4+ to WSTN. As can be
deduced from the table, VWM concentrations of each species were comparable
and NH4+ exhibited the highest concentration, with a value of
28.7 µmol N L-1. The VWM concentrations of WSON and
NO3- were 21.5 and 23.3 µmol N L-1, respectively.
Considering their relative contributions to WSTN, WSON and NO3-
account for 29 and 32 % of the WSTN, whilst NH4+ represented 39 %
of the observed WSTN concentration in rainwater.
Comparison of WSON in aerosol and rain with data from the
literature
The concentrations of WSON in marine aerosols and rain samples collected from
different sites located around the Mediterranean, Atlantic and Pacific
regions are illustrated in Table 3. Comparing the current WSON values with
those reported in the literature is challenging due to (i) different applied
sampling periods, sampling and measurement techniques and (ii) the high
uncertainty associated with the estimation of WSON. Furthermore, within the
literature there is a lack of information defining the uncertainty of WSON
though there is a substantial statistical knowledge. Keene at al. (2002), in
particular, have highlighted the tendency in the literature to neglect
negative values or substitute such values with zero instead when calculating
the WSON from the difference between WSTN and WSIN. As these authors have
highlighted, the omission or substitution of such values inevitably would
result in a positive bias in the WSON concentrations.
Comparison of WSON concentrations in aerosol (nmol N m-3) and
rain (µmol N L-1) samples for different sites of the world.
Aerosol (nmol N m-3)
WSON
NS
SP
Reference
Mediterranean Sea
Erdemli, Turkey
23.8
674
2014–2015
This study
Erdemli, Turkey
29
39
2000
Mace et al. (2003a)
Finokalia, Crete
17.1
65
2005–2006
Violaki and Mihalopoulos (2010)
Pacific Ocean
Hawaii
4.1
16
1998
Cornell et al. (2001)
Tasmania
5.3
24
2000
Mace et al. (2003b)
Taiwan
75.9
77
2006
Chen et al. (2010)
Xi'an, China (PM2.5)
300
65
2008–2009
Ho et al. (2015)
Atlantic Ocean
Barbados
1.3
57
2007–2008
Zamora et al. (2011)
Amazon, dry season
61
37
1999
Mace et al. (2003c)
Amazon, wet season
3.5
27
1999
Mace et al. (2003c)
Indian Ocean
Amsterdam Island
1
42
2005
Violaki et al. (2015)
Rainwater (µmol N L-1)
WSON
NS
SP
Reference
Mediterranean Sea
Erdemli, Turkey
21.5
23
2014–2015
This study
Erdemli, Turkey
15
18
2000
Mace et al. (2003a)
Finokalia, Crete
18
18
2003–2006
Violaki et al. (2010)
Pacific Ocean
Tahiti*
4.8
8
Cornell et al. (1998)
Hawaii
2.8
17
1998
Cornell et al. (2001)
Tasmania
7.2
6
Mace et al. (2003b)
North China Plain, China
103
15
2003–2005
Zhang et al. (2008)
Kilauea, Hawaii
6.5
20
1998
Cornell et al. (2001)
Atlantic Ocean
Bermuda
5.6
5
1994
Cornell et al. (1998)
Mace Head
3.3
7
Cornell et al. (1998)
Norwich, UK
33
12
Cornell et al. (1998)
Virginia, United States
3.1
83
1996–1999
Keene et al. (2002)
Delaware, United States
4.2
50
1997–1999
Keene et al. (2002)
New Hampshire, United States
0.6
12
1997
Keene et al. (2002)
* RC, NS and SP refer to relative contribution of WSON to WSTN, number of samples and sampling period, respectively.
The daily variation in the concentrations of (a) WSON,
(b) NO3- and (c) NH4+ (nmol N m-3)
together with rain amount (mm) from March 2014 to April 2015 for PM10.
![]()
In general, the lowest concentrations in aerosols were found in those derived
from remote or pristine marine environments. The WSON concentrations in the
atmosphere over the Indian (Amsterdam Island: 1.0 nmol N m-3, Violaki
et al., 2015), Atlantic (Barbados: 1.3 nmol N m-3, Zamora et al.,
2011) and Pacific Ocean (Hawaii, Oahu: 4.1 nmol N m-3, Cornell et
al., 2001, Tasmania: 5.3 nmol N m-3, Mace et al., 2003b) were at
least 4 times less than those observed for the eastern Mediterranean (Erdemli:
23.8 nmol N m-3, this study; Finokalia: 17.1 nmol N m-3,
Violaki and Mihalopoulos, 2010). These lower values might be attributed to
(i) the absence of the strong anthropogenic sources in the vicinity of the
sampling sites, (ii) the dilution of the WSON originating from long-range
transport via both dry and wet deposition and/or (iii) small contributions
from non-land-based local emissions such as sea salt and algal blooms. The
highest WSON concentrations emerged particularly over China (Ho et al., 2015,
concentration of WSON measured in PM2.5) and Taiwan (Chen et al., 2010),
with values above 70 nmol N m-3. As stated in Chen et al. (2010) WSON
concentrations at these sampling sites were markedly influenced by
anthropogenic activities such as fossil fuel combustion and human-induced
biomass burning. Concentrations over the Amazon (Mace et al., 2003c) in the
dry season (61 nmol N m-3) have also been noted. Such high values
were ascribed to natural fires (Mace et al., 2003c). The mean WSON
concentration at Erdemli (23.8 nmol N m-3) was comparable to that
reported previously for the same site (29 nmol N m-3, Mace et al.,
2003a). In contrast, the present WSON concentration was almost 1.5 times
higher than that observed at Finokalia (Violaki and Mihalopoulos, 2010).
The reported WSON values for rain also exhibited the lowest concentrations in
those derived from remote or pristine marine environments, such as Hawaii
(2.8 µmol N L-1, Cornell et al., 2001). The highest WSON
concentrations were observed in China (North China Plain:
103 µmol N L-1, Zhang et al., 2008) and in Norwich, UK
(33 µmol N L-1, Cornell et al., 1998). These
high values were again attributed to the anthropogenic sources.
Temporal variability of water-soluble nitrogen species in aerosol
Erdemli
Figure 1 illustrates daily variation of the water-soluble nitrogen species in
aerosol samples together with the daily rainfall from March 2014 to
April 2015. The same figure also presents the concentrations in rainwater
samples collected between October 2014 and April 2015. It is clear that WSON
concentrations exhibited large variation from one day to another day. The
daily variability in the concentration of WSON may be an order of magnitude.
Such variability has also been reported in Atlantic (Zamora et al.,
2011), Pacific (Chen et al., 2010) and eastern Mediterranean marine aerosols
(Violaki and Mihalopoulos, 2010). These studies demonstrated that the daily
change in the concentrations of WSON arises from a combination of
(a) meteorological parameters (such as rain, temperature and wind
speed/direction), (b) chemical reactions, (c) history of air masses back
trajectories and (d) source emission strength.
In general, lower concentrations of WSON were found to be associated with
rainy days. To serve as an illustration, one of the lowest WSON
concentrations was observed on 19 October 2014, after two consecutive days of
rainfall, with a value of 6 nmol N m-3. In contrast, one of the
highest observed WSON concentrations (66.1 nmol N m-3) was detected
on 2 March 2014, when the air mass back trajectories were associated with
south/southwesterly airflow (for more details, see Sect. 3.4). Another high
concentration of WSON was observed on 5 July 2014, with a value of
66 nmol N m-3. A total of 94 % of the WSON was present in the coarse
mode; however, during this event there was no intense dust intrusion either from
the Sahara or from the Middle Eastern deserts. The corresponding OMI-AI and
nssCa2+ (33 nmol m-3) also support this observation (see
Fig. 2). Lower layer air mass back trajectories (1000 and 2000 m)
demonstrated that Erdemli was under the influence of north/northwesterly
airflow from Turkey after passing over Turkey's largest cultivated plain,
Konya. Thus, this high value might be attributed to resuspension of the soil
affected by intense agricultural activities. On 20 January 2015 the WSON
concentration was 60 nmol N m-3, 72 % being present in the fine
mode. For this event, the NH4+ concentration was
20 nmol N m-3, 2 times higher than the observed arithmetic mean in
winter. Corresponding trajectories, AOD (aerosol optical depth) and AC
(Ångström component) images are presented in Fig. 3. Airflow at 1 km showed
air mass flow arriving at the sampling site from Turkey. AOD values over the
sampling site and coastline of northeastern Mediterranean ranged from 0.2 to
0.5, whilst AC values demonstrated that the region was dominated by fine
particles. Based on the above indicators, it may be concluded that anthropogenic
sources were dominant.
Three-day back trajectories showing the transport of air masses
1000 m (black circle), 2000 m (black star), 3000 m (black square) and
4000 m (black triangle) on 5 July 2014 for Erdemli. Aerosol index (AI) from
OMI (Ozone Mapping Instrument) distribution also illustrated with a color bar
from grey to dark red.
![]()
Three-day back trajectories showing the transport of air masses
1000 m (black circle), 2000 m (black star), 3000 m (black square) and
4000 m (black triangle) on 20 January 2015 for Erdemli. The aerosol optical
depth (AOD, a) and Ångström component (AC, b) from MODIS
(Moderate Resolution Imaging Spectroradiometer) distribution are also
demonstrated with a color bar from grey to dark red.
![]()
A summary of the statistical analyses of the seasonal dataset of aerosol-associated WSON, NO3- and NH4+ is shown in Table 4. The
Mann–Whitney U test indicated that there was a statistically significant
difference among seasons, such that summer > spring ≈ winter > fall. The arithmetic mean value of WSON in the summer was
found to be 1.3 and 2.0 times greater than that observed for spring/winter and
fall, respectively. Percent WSON contributions of coarse mode for winter
(50 %), spring (50 %) and fall (55 %) were comparable. However,
WSON was chiefly associated with coarse particles in summer, amounting to
83 %. This high value in summer might be due to the absence of rainfall
(see Fig. 1) and enhanced resuspension of cultivated soil in the region. In
summer, the mean concentration of NH4+ was almost 2.4 times larger
than all other seasons. The mean water-soluble NO3- in summer was
1.4 higher than that of spring. High NH4+ and NO3-
concentrations in summer might be attributed again to the absence of rainfall
and increase in incoming radiation. Similar results have been reported for
the eastern Mediterranean (Bardouki et al., 2003).
Seasonal statistical summary of the WSON, NO3-,
NH4+, WSTN (nmol N m-3) and nssCa2+ (nmol m-3) in
aerosol samples collected at Erdemli from March 2014 to April 2015.
Aerosol
Winter
Spring
Summer
Fall
species
WSON
33 ± 16
28 ± 13
41 ± 11
20 ± 10
Coarse / PM10 (%)
50
50
83
55
NO3-
7 ± 5
15 ± 12
21 ± 7
9 ± 8
NH4+
10 ± 12
11 ± 9
24 ± 16
10 ± 13
nssCa2+
28 ± 13
28 ± 13
28 ± 13
41 ± 11
Number of samples
47
79
46
44
Meteorology
Winter
Spring
Summer
Fall
parameter
T (∘C)
11 ± 3
16 ± 3
27 ± 12
20 ± 15
Rain (mm)
78
118
0.5
132
Number of rain events
16
16
2
15
Influence of mineral dust episodes on WSON aerosol
concentrations
As is well documented, the eastern Mediterranean Sea is heavily impacted
by mineral dust episodes originating from Sahara and Middle Eastern deserts
(Kubilay and Saydam, 1995; Kubilay et al., 2000, Koçak et al., 2004a, b,
2012).
For the current study between March 2014 and April 2015, water-soluble
non-sea salt calcium concentrations higher than 50 nmol m-3
(2000 ng m-3 as a threshold value) were defined as mineral “dust
events”. These events were additionally confirmed using air mass back
trajectories and OMI-AI. However, it is worth mentioning that for samples
containing concentrations of nssCa2+ less than 50 nmol m-3,
mineral dust transport from Sahara and Middle Eastern deserts to the sampling
site may not be excluded, particularly in winter. Yet, the application of such
an arbitrary value is inevitable since it provides simplicity to explore if
there is any influence of mineral dust intrusion on WSON.
For example, one of the highest WSON concentrations (66.1 nmol N m-3)
was observed on 2 March 2014, when the air mass back trajectories were
associated with south/southwesterly airflow. During this event, nssCa2+
and NO3- showed a dramatic increase in their concentrations compared
to the values observed during the previous day, reaching up to 429 and
60 nmol m-3, respectively. The OMI (Ozone Mapping Instrument) aerosol
index (AI) and 3-day backward trajectory (1, 2, 3 and 4 km altitudes)
air masses arriving at the Erdemli sampling site on 2 March 2014 are shown in
Fig. 4. As can be seen from the figure, all air masses (except at 1 km
altitude) originated from north Africa, whereas the back trajectory for 1 km
altitude exhibited airflow from the Middle East. Hence, it is suggested that the
sampling site was under the influence of mineral dust transport originating
from desert regions located in the Middle East and north Africa. In support of this,
the OMI-AI diagram clearly indicates a large dust plume over the eastern Mediterranean between coordinates 20–45∘ N and 15–40∘ E.
The aerosol index was found to be very high over the northeastern
Mediterranean, ranging from 2.0 to 4.5. During this dust episode, 85 % of
the WSON was associated with the coarse fraction, which further supports
mineral dust being a main source of water-soluble organic nitrogen.
Three-day back trajectories indicating the transport of air masses
1000 m (black circle), 2000 m (black star), 3000 m (black square) and
4000 m (black triangle) on 2 March 2014 for Erdemli. The aerosol index (AI) from
OMI (Ozone Mapping Instrument) distribution is also illustrated with a color bar
from grey to dark red.
![]()
Arithmetic mean concentrations together with corresponding standard
deviations of WSON, NO3-, NH4+ and nssCa2+ for dust and
non-dust events are presented in Fig. 5. As can be deduced from the diagram
(except for NH4+), WSON, NO3- and nssCa2+ indicated
a distinct difference between dust and non-dust events. Indeed, the application
of the nonparametric Mann–Whitney U test indicated statistically significant
differences between dust and non-dust events for WSON (p < 0.03),
NO3- (p < 0.00002) and nssCa2+ (p < 0.000001),
whereas no statistically significant difference was observed for
NH4+, (p=0.56). The crustally derived nssCa2+ and
anthropologically derived NO3- for dust events had arithmetic means of
95.8 nmol m-3 and 26.1 nmol N m-3, which were almost 4 and
2 times higher than those observed for non-dust events, respectively.
Such an increase in concentrations during dust events for these species has
been previously reported in the eastern Mediterranean (Koçak et al.,
2004b). Similarly, the arithmetic mean of WSON (38.2 nmol m-3) during
dust events was 1.3 times higher compared to the value observed during
non-dust events (29.4 nmol m-3). Percent contributions of coarse WSON
for dust and non-dust events were almost identical, being 58 and 60 %,
respectively. A similar enrichment of WSON during dust events has been
reported for Erdemli (Mace et al., 2003a), the Yellow Sea (Shi et al., 2010) and
Finokalia (Violaki and Mihalopoulos, 2010). In addition, Griffin et
al. (2007) have demonstrated a significant difference between dust and
non-dust events for bacterial- and fungal-colony-forming units at Erdemli, the
former being much greater. Thus, it might be speculated that this enhancement
during dust events can be due to (a) mineral-dust-borne microorganisms, and/or
(b) interaction (e.g., adsorption, acid-based reaction) between mineral
dust and organic nitrogen compounds.
Arithmetic means together with corresponding standard deviations of
WSON, NO3-, NH4+ and nssCa2+ for dust and non-dust
events at the Erdemli site. Orange and blue bars denote arithmetic means for dust
and non-dust, respectively. The black vertical line shows standard deviation.
![]()
Arithmetic means along with standard deviations of WSON,
NO3-, NH4+ (nmol N m-3) and nssCa2+
(nmol m-3) in aerosol samples as a function of the classified airflow
corresponding to 3-day air mass back trajectories reaching Erdemli.
Airflow
WSON
Coarse / PM10 (%)
NO3-
NH4+
nssCa2+
Middle East
33 ± 12
61
12 ± 12
13 ± 15
48 ± 71
North Africa
36 ± 16
58
18 ± 11
12 ± 14
46 ± 38
Turkey
32 ± 13
63
15 ± 10
19 ± 15
23 ± 9
Eastern Europe
26 ± 14
49
10 ± 9
10 ± 8
21 ± 9
Western Europe
26 ± 14
48
10 ± 8
11 ± 9
20 ± 7
Mediterranean Sea
22 ± 10
27
10 ± 8
8 ± 6
19 ± 8
Impact of airflow on WSON
Arithmetic mean concentrations together with corresponding standard
deviations for water-soluble nitrogen species and nssCa2+ in aerosol
samples according to categorized air mass sectors (at 1 km) are presented in
Table 5. WSON concentrations for the Middle East, north Africa and Turkey were
comparable and arithmetic mean values were, respectively, 33, 36 and
32 nmol m-3. Correspondingly, mean WSON concentrations for eastern
Europe, western Europe and the Mediterranean Sea were 26, 26 and
22 nmol m-3, being at least 1.2 times lower than those observed for
the Middle East, north Africa and Turkey (Mann–Whitney U test, p<0.05).
Coarse-mode contributions of WSON for air flow from the Middle East (61 %),
north Africa (58 %) and Turkey (63 %) ranged from 58 to 63 %.
However, lower coarse-mode contributions were observed when air flow
originated from eastern Europe (49 %), western Europe (48 %) and the Mediterranean Sea (27 %). The highest NO3- concentrations were
associated with airflow from north Africa and Turkey, with a value of 18 and
15 nmol N m-3, respectively, and there was a statistically
significant difference compared to the remaining air mass sectors (p>0.05). The mean concentrations of NO3- for air masses
derived from north Africa and Turkey were at least 1.3 times larger than those
calculated for the Middle East, eastern Europe, western Europe and
Mediterranean Sea air sectors (p>0.05). NH4+ had the highest
concentration under the influence of airflow derived from Turkey. For this
airflow, detected concentration was 1.5–2.4 times greater than that
calculated for other air mass sectors. The Mann–Whitney U test showed that
there was a statistically significant difference in the nssCa2+
concentrations. Arithmetic mean concentrations of nssCa2+ in the Middle
East and north Africa were approximately 2 times higher compared to the
remaining air masses. As expected, these two airflows were primarily
influenced by crustal material due to sporadic dust events originating from
deserts located in north Africa and the Middle East.
Source apportionment of WSON from positive matrix factorization for
PM10 at Erdemli.
![]()
Source apportionment for WSON in aerosol
A number of studies have discussed the possible sources of WSON in aerosol
material by applying either simple correlation analyses (Mace et al., 2003a;
Violaki and Mihalapoulos, 2010; Ho et al., 2015) or multivariate factor
analyses (FA; Chen and Chen, 2010), including PMF (Chen et al., 2010). Usage of
correlation analyses is useful when the numbers in sample populations are
limited; however large datasets are required in order to carry out PMF and
FA. Direct and indirect emissions of WSON from the sea surface have been
demonstrated (Miyakazi et al., 2011; Altieri et al., 2016). Previous studies
in the eastern Mediterranean have observed WSON to be associated with mineral
dust (Mace et al., 2003a; Violaki and Mihalopoulos, 2010). As stated by Mace
et al. (2003a), WSON might either have originated from mineral dust or
might have been carried by dust events owing to adsorption of gaseous organic nitrogen
compounds onto preexisting particles. In addition, Violaki and
Mihalapoulos (2010) have shown fossil fuel and biomass burning as sources of
WSON in the eastern Mediterranean atmosphere.
Figure 6 describes the potential sources of WSON by applying PMF 5.0. The
predominant two factors were chiefly found to be related with WSTN. The first
factor had a high-loading for NH4+ with a value of 0.81 and a
moderate loading of SO42- (0.45). As expected, the factor
contribution plot (not shown) indicated a summer maximum, demonstrating
accumulation of these particles due to the absence of rain and enhanced
gas–particle formation under the prevailing conditions (high temperature
and solar radiation). The equivalent ratio of NH4+ and SO42-
for this factor was 0.79, indicating (NH4)HSO4 formation (Koçak
et al., 2007). A total of 60 % of the air mass trajectories was found to be
originated from Turkey when the first highest 20 % of the factor loading
were considered. Consequently, this factor might principally be ascribed to
regional sources such as urban agglomerations (Ankara, İzmir and
İstanbul) and industrial activities (particularly the Marmara region). The
second factor explained 77 % of the NO3- variation and described
17 and 10 % of the SO42- and NH4+ variation,
respectively. This group was also associated with cations such as Na+
(11 %), K+ (7 %), Mg2+ (22 %) and Ca2+ (29 %),
implying reactions mainly between acidic nitrate and alkaline species. It has
been shown that emissions of Cl- and NO3- result from motor
vehicles (Lim at al., 2010). Taking into account the absence of Cl-,
this factor may be attributed to combustion. The first and second factors
accounted for 20 and 22 % of the variability in WSON, respectively. It
might, therefore, be argued that the variability of WSON in the first group
resulted from the reaction between volatile organic N and ammonium sulfate
aerosols, whilst the variability of WSON explained by the second factor was as
a result of the reaction between volatile organic compounds and NOx
and/or neutralization of acidic nitrate by alkaline nitrogen-containing
compounds such as urea and amine. The third factor was heavily influenced by
Cl- (0.8) and Na+ (0.70), while it was moderately impacted by Mg2+ and
K+. This factor is likely due to sea salt formation. The fourth factor
was predominantly impacted by Ca2+ and hence may be attributed to
crustal material. Crustal sources explained 10 % of the WSON variability.
The final defined factor had a moderate loading of WSON (EV = 0.43,
explained 43 %) while it was affiliated with Na+ (0.15), K+
(0.22) and Mg2+ (0.24). The factor contribution diagram shows the highest
values to be in summer (not shown) and hence it can be attributed to resuspension
of the soil particularly affected by intense agricultural activities.
Atmospheric depositions of N species and implications
regarding marine production
The atmospheric dry (n=337; 21.3 mmol N m-2 yr-1) and wet
(n=23; 36.7 mmol N m-2 yr-1) deposition fluxes of WSON,
NO3-, NH4+ and WSTN from March 2014 and April 2015 are
demonstrated in Table 6. The atmospheric deposition of water-soluble total
nitrogen (57.8 mmol N m-2 yr-1) was chiefly originated from wet
deposition (36.7 mmol N m-2 yr-1), amounting to 63 % of the
total atmospheric deposition. This difference might be attributed to the
water-soluble ammonium; for instance, the atmospheric deposition of
NH4+ (15.6 mmol N m-2 yr-1) was dominated by wet
deposition, contributing 92 % of the total ammonium atmospheric flux.
In contrast, the atmospheric fluxes of WSON and NO3- were more or less
equally influenced by both deposition modes. Corresponding WSON
(9.8 mmol N m-2 yr-1) and NO3-
(10.0 mmol N m-2 yr-1) contributions to dry deposition were
found to be 46 and 48 % respectively. In contrast, NH4+
(1.3 mmol N m-2 yr-1) was only estimated to contribute 6 %
of the total deposition. Wet deposition of nitrogen was impacted by WSON
(10.8 mmol N m-2 yr-1), NO3-
(11.7 mmol N m-2 yr-1), and NH4+
(14.3 mmol N m-2 yr-1) in the increasing order
29 % < 32 % < 39 %. On average, WSON accounted for
36 % of the total atmospheric deposition of WSTN. The atmospheric
deposition of the dissolved inorganic nitrogen
(DIN = 37.3 mmol N m-2 yr-1) was found to decrease about
45 % compared to the value reported by Koçak et al. (2010,
DIN = 70 mmol N m-2 yr-1). The reason for this decrease is
beyond the scope of this article; nonetheless, there is a need to understand how
the DIN flux changed from the beginning of the 2000s to 2015.
Atmospheric dry (337 samples) and wet (23 samples) deposition of
WSON, NO3-, NH4+ and WSTN together with their relative
contributions at Erdemli during the period of March 2014 to April 2015.
Species
Fd
Relative
(mmol N m-2 yr-1)
contribution
WSON
9.8
46
NO3-
10.0
48
NH4+
1.3
6
WSTN
21.1
Species
Fw
Relative
(mmol N m-2 yr-1)
contribution
WSON
10.7
29
NO3-
11.7
32
NH4+
14.3
39
WSTN
36.7