Atmospheric mercury vegetation/air fluxes and ... · Atmospheric mercury vegetation/air fluxes and concentrations in contaminated sites of the Tagus Estuary, Portugal Sara Justinoa*,
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Atmospheric mercury vegetation/air fluxes and concentrations
in contaminated sites of the Tagus Estuary, Portugal
Sara Justinoa*, Nelson O’Driscollb, João Canárioa
aCentro de Química Estrutural, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, Lisboa, Portugal
bDepartment of Earth & Environmental Sciences, Acadia University; Wolfville, Nova Scotia; Canada
*sara_justino@hotmail.com
Abstract:
This study aims to evaluate vegetation-atmosphere Hg(0) flux patterns and Hg(0) in air concentrations, from two sites on the Tagus Estuary, Portugal (one low mercury background site, and one high mercury industrial site), and also assess if there is any correlation with weather variables (temperature, radiation, humidity, wind speed and direction). In addition, this study examines the possible relationships with Sarcocornia fruticosa and Halimione portulacoides. No significant correlations appeared between vegetation-air mercury flux and any of the weather variables for both sites, due to the fact that the calculated fluxes were near detection limits for the background site and, for the industrial site, local contamination resulted in the variability of data. For the background site, a strong correlation was found between atmospheric Hg(0) concentrations and solar radiation, identifying this variable as one of the primary drivers of Hg(0) concentrations in air. Temperature and relative humidity were related to solar radiation, and also significantly correlated with Hg(0) in air. For the industrial site, weak negative correlations were found between mercury vegetation – air flux and temperature, and solar radiation. There was also a weakly positive correlation with relative humidity. It was hypothesized that this site is being affected by local atmospheric Hg(0) emissions from the W-WNW directions (direction of Solvay chlor alkali factory), making the measurements of Hg(0) flux from vegetation variable. No significant differences in trends were observed for Hg(0) vegetation-air fluxes for Sarcocornia fruticosa and Halimione portulacoides for the background site, and differences observed for the industrial site may be caused by large background Hg(0) concentrations and variability in the data.
key words: Hg fluxes; contamination; Salt-marsh plants; Tagus Estuary;
1. Introduction
Mercury is a naturally occurring, persistent,
and toxic metal that is present in all
environmental compartments. It is a global
pollutant and due to its long-range
transport, it can be found in remote
ecosystems such as Polar Regions (Black,
Campbell, & Harmon, 2010).
Due to some of its properties, such as low
reactivity and low solubility in water, Hg(0)
has a residence time in the atmosphere on
the order of one year, facilitating its
distribution and deposition on a global scale
(UNEP, 2013). It can be emitted to the
atmosphere from a variety of point and
diffuse sources, where it is dispersed and
transported in the air, deposited to the earth
and stored in or redistributed between
water, soil/sediments, and atmospheric
compartments.
While in the atmosphere, mercury can
participate in various processes of
chemical, physical or photochemical nature,
facilitating its oxidation to a more soluble
and reactive form, divalent mercury Hg(II),
and its allocation into aquatic and terrestrial
compartments. Ultimately, when in those
compartments, it can be converted to
methylmercury, CH3Hg (I) or MeHg (UNEP,
2013).
The fact that MeHg can be bioaccumulated
throughout the food web represents one of
the main environmental concerns of the
ecotoxicology of mercury, justifying the
need to study its biogeochemical cycle in
detail and, in particular, its transfer
processes between environmental
compartments (Qureshi, MacLeod,
Scheringer, & Hungerbu, 2009).
Since anthropogenic atmospheric Hg (0)
can be recycled through and re-emitted
from vegetation, it remains unclear if the
biosphere is a long-term source or sink of
Hg. Having in mind that nearly 30% of the
earth's land surface area is covered by
vegetation (approximately 4×109 ha), it is
crucial to quantify the role of vegetation in
mercury emissions, on both regional and
global scales, in order to develop accurate
mass balances for global movements.
However, these mercury emissions are
dependent upon many variables such as
climate, soil chemistry, microbiology, as
well as species specific factors such as
mercury uptake from the atmosphere,
atmospheric deposition to foliage and
mercury uptake from roots [(Lodenius,
1998); (Rea, Lindberg, Scherbatskoy, &
Keeler, 2002); (Lodenius, Tulisalo, &
Soltanpour-Gargari, 2003)].
2. Methods
The study was carried on the Tagus
Estuary Natural Park, Portugal, (Figure 1),
on February and March 2014. The first site
was located on “Reserva Natural do
Estuário do Tejo”, a low-contaminated site,
and the second near the Solvay complex, in
Póvoa de Stª Iria, a contaminated site (J.
Canário, Vale, & Caetano, 2005).
Figure 1- Sampling locations for the non-
contaminated and contaminated site, Tagus
estuary (red balloons).
2.1 Site description
The Tagus estuary is located on the central
west coast of Portugal, covering about 325
km2, with an intertidal area of 120 km
2,
being one of the largest estuaries in
Europe.
From tradional activities such as fishery and
salt extraction, it was on the XX century that
it became an important sea port, with a
number of industries instaling on its
margins. At the same time, the population
living on the marges began to grow, all of
this causing a great amount of pressure on
the ecosystems and increasing pollution
loads (J. Canário et al., 2005).
This anthropogenic pressure was estimated
to be caused by 600 pollution sources from
different origins, both urban and industrial,
from difused sources (agriculture for
example) and from atmospheric diposition
(J. Canário et al., 2005).
Regarding Mercury, it is considered to be
one of the biggest pollutants in the Tagus
estuary, being its “hot spots” the industries
located on Cala do Norte, near Póvoa de
Stª Iria, in the CUF channel near Quimigal,
Barreiro, and industries not identified in
Alcochete (Figueres, Martin, Meybeck, &
Seyler, 1985).
A number of studies concerning total Hg
and MeHg concentrations in sediments in
the Tagus Estuary showed that the
proportion of MeHg to the total Hg varies in
the entire estuary from 0.02 to 0.4%.
Surface sediments presented 23 tons of Hg
stored in the first 5 cm of sediments,
whereas 24 kg in the form of Methylmercury
[(J. Canário & Vale, 2004; João Canário et
al., 2010; João Canário, Branco, & Vale,
2007)]
2.2. Mercury analyzer
For total mercury analysis, it was used a
Tekran 2537A automatic analyzer. Briefly,
the process of this instrument consists on
the amalgamation of mercury on a pure
gold surface, followed by thermodesorption,
and analysis by cold vapor atomic
fluorescence spectrophotometry (Bloom
and Fitzgerald , 1988). The dual cartridge
design allows alternate sampling and
desorption, providing duplicate sequential
measurements that help confirm reliable
and stable instrument operations. The
Tekran has a precision of 2% and an
average detection limit for total gaseous
mercury of 0.06 ng m-3
[(Poissant, Pilote,
Yumvihoze, & Lean, 2008; Tekran, 2001)].
2.3. Dynamic flux chamber and bag
The dynamic flux chambers and dynamic
flux bags were used to measure foliage/air
Hg(0) exchange. The chambers were made
of Teflon (PFA), presenting an inner
diameter of 89 mm, outer diameter of 119
mm, height of 241 mm and a volume of 2.2
L. In order to not alter their shape and to
prevent contact with the leaves, the
chambers were clamped to an external
steel frame. The dynamic flux bag was
composed of Tedlar®, used in site two for
the measurements of the Halimione
portulacoides, with the external dimensions
of 900 mm X 1250 mm and a maximum
volume of 200 L. Details about this flux
chamber can be found in (Poissant L. ,
Pilote, Xu, Zhang, & Beauvais, 2004).
The mercury flux (ng m-2
hr-1
) from the
dynamic flux chamber and bag (F) was
computed as it follows:
Equation 1- Flux equation for a flux chamber
Where Co is the mercury concentration
outside the flux chamber (ng m-3
), Ci is the
mercury concentration inside the flux
chamber (ng m-3
), AS is the area of
substrate covered by the flux chamber (m2),
and Q is the flow rate of air through the
chamber (m3 h
-1).
For both chamber and bag, an inlet
sampling tube was connected to the top
center and an outlet sampling tube to left
bottom of the chamber/bag. Both tube’s
material was Teflon, allowing ambient air to
flow and ensuring a steady state operation,
with no measurable pressure gradients
within the chamber/bag.
In both cases, an external air pump
(Barnant Air Cadet) with an average flow
rate of 1.5 L min-1
and a solenoid valve
system were used to create a homogenous
internal Hg(0) concentration, avoiding the
stagnation of air in the system (which could
result in the adsorption of mercury on the
Teflon lines). A mass flow meter was
connected between the air pump and the
solenoid valves in order to confirm the flow
rate. Connecting the Tekran system to the
dynamic flux systems were Teflon PFA
sampling lines and fittings, with and inner
diameter of 4, 76 mm.
2.4. Mercury Analyses in plants
The total Hg analyses were performed on
“Instituto Português do Mar e Atmosfera”,
IPMA, with a LECO Advanced Mercury
Analyzer (AMA-254). Concerning its
detection limits, these range from a
minimum detection limit of 0.01 to a
maximum of 500 ng of Hg. Lastly, in order
to quantity the total mercury, the software
that comes with the analyzer has two
calibration curves (0-40) and (40-500) ng
(Leco, 2002).
Two replicates of each sample were
measured and averaged, and the results
presented on the basis of dry weight.
Dogfish dorsal muscle (DORM-1) certified
reference material for total mercury was
analyzed according to the same procedures
as the samples for the AMA-254 calibration
with a recovery percentage of 98%. The
average for the duplicates with total
mercury standards analyzed was <5%.
2.5 Quality Assurance and Control
Quality assurance and control procedures
were implemented throughout the field and
laboratory sampling and analysis process.
Quality assurance consisted on the
verification of the accuracy of the
permeation source by manual injection
recovery tests (>95% recovery of 10 pg
spike), calibrations by automatic injections
and spike recovery tests. In addition, before
flux measurements, blanks on the dynamic
flux chambers and bags were performed in
the laboratory by measuring inlet and outlet
Hg(0) concentrations with no vegetation
inside the chamber/bag. The detection limit
of 7,19 ng m-2
hr-1
was obtained for the
Hg(0) flux, and for the Hg(0)
concentrations, 1.24 ng m-3
. These
detection limits were calculated as 3 times
the standard deviation of the previous set of
blank readings.
Quality controls were applied on the field,
for example, recalibrations when significant
0
1
2
3
4
0 3 6 9
12 15 18
15
:05
1
8:0
5
21
:05
0
:05
3
:05
6
:05
9
:05
1
2:0
5
15
:05
1
1:3
0
13
:45
1
6:0
0
18
:15
2
0:3
0
22
:45
1
:00
3
:15
5
:30
7
:45
1
0:0
0
14
:10
1
6:2
5
18
:40
2
0:5
5
23
:10
1
:25
3
:40
5
:55
8
:10
Hg(
0)
Co
nce
ntr
atio
ns
(ng
m-3
)
Tem
pe
ratu
re (
° C
)
Time
instrument changes were made, such as
changing of sensitivity or flow rates. As for
the meteorological parameters, at both sites
they were measured using the same
meteorological stations in order to minimize
instrumental differences.
2.6. Meteorological parameters
Meteorological parameters were monitored
and recorded during the field studies,
including air temperature, solar radiation,
wind speed, direction and relative humidity,
using a David Wireless Vantage Pro2™
Plus. In addition, soil surface temperature
was monitored using HOBO node wireless
sensors.
3. Results and discussion
3.1. Vegetation-air fluxes variations
No significant correlations were found
between vegetation mercury flux and any of
the studied variables at either the
background site or the industrial site.
This may be attributed to the fact that the
calculated vegetative fluxes were near
detection limits for site 1 and, for site 2,
local contamination resulted in an unstable
ambient air concentration and a wide
dispersion of mercury flux values.
3.2. Atmospheric Mercury
Concentrations for Site 1
The median concentrations in site 1 were
1.81 ± 0.49 ng m-3
(n=783), whilst the
maximum value registered was 3.53 ng m-2
hr-1
and the minimum 1. 18 ng m-2
hr-1
.
The measured atmospheric Hg(0)
concentrations were in good agreement
with the average background
concentrations in urban areas for Europe
Union, which are between 0.1- 5 ng m-3
for
(World Health Organization, 2000).
Figure 2 presents peaks of higher
atmospheric mercury concentrations,
occurring between 10:20-14:00, which may
suggest a strong influence of solar radiation
and temperature variables controlling air
concentrations of mercury at the site.
These peaks are probably due to the
increased surface reduction of mercury and
volatilization from all sources (ocean water,
sediments, and vegetation), which result in
higher air concentrations with solar
radiation.
3.2.1. Patterns in atmospheric mercury
concentrations with meteorological
variables for Site 1
The Hg(0) concentrations measured
present a strong correlation with the
variables solar radiation and relative
humidity, respectively, a positive and a
negative one (for solar radiation, Pearson
correlation coefficient = 0.81, p-value
<0.001, n=789 and for relative humidity,
Pearson correlation coefficient = -0.73, p-
value <0.001, n=783). As for temperature, a
good positive correlation is confirmed
(Pearson correlation value of 0.64 and p-
value <0.001, n=783), and for wind speed,
a weak correlation was found (Pearson
correlation coefficient -0.12, p-value <0.001,
n=783).
Grey Line- Temperature Black Line- Hg(0) Concentrations
0,00
1,00
2,00
3,00
4,00
0
200
400
600
800
1000 1
5:0
5
17
:50
20
:35
23
:20
2:0
5
4:5
0
7:3
5
10
:30
13
:15
16
:00
18
:45
21
:30
0:1
5
3:0
0
5:4
5
8:3
0
13
:10
15
:55
18
:40
21
:25
0:1
0
2:5
5
5:4
0
8:2
5
Hg(
0)
Co
nce
ntr
atio
ns
(ng
m-3
)
Sola
r R
adia
tio
n (
W m
−2)
Time
0
1
2
3
4
0
2
4
6
8
15
:05
17
:35
20
:05
22
:35
1:0
5
3:3
5
6:0
5
8:3
5
11
:15
13
:45
16
:15
18
:45
21
:15
23
:45
2:1
5
4:4
5
7:1
5
9:4
5
14
:10
16
:40
19
:10
21
:40
0:1
0
2:4
0
5:1
0
7:4
0
Hg(
0)
Co
nce
ntr
atio
ns
(ng
m-3
)
Win
d S
pe
ed
(m
s-1
)
Time
0
1
2
3
4
5
25
45
65
15
:05
17
:35
20
:05
22
:35
1:0
5
3:3
5
6:0
5
8:3
5
11
:15
13
:45
16
:15
18
:45
21
:15
23
:45
2:1
5
4:4
5
7:1
5
9:4
5
14
:10
16
:40
19
:10
21
:40
0:1
0
2:4
0
5:1
0
7:4
0
Hg(
0)
Co
nce
ntr
atio
ns
(ng
m-3
)
Re
lati
ve H
um
idit
y (%
)
Time
Figure 2- Atmospheric Hg(0) concentrations and meteorological variables for site 1, respectively,
solar radiation, wind speed, respectively solar radiation, temperature.
In relation to wind direction, it was
observed that 99% of the measured
concentrations are between the winds SW-
N directions (225°- 360°), Table 1. The
remaining 1% present in other directions
could affect the data, if the values were
anomalous, but in this case, since their
average is only slightly lower, they do not
significantly interfere (with these
concentrations the average is 1.81 0.49
and without is 1.81 0.19). Therefore, the
hypothesis of inputs of Hg(0) from the
vicinity cannot be assessed since there is
not enough variability in the data.
A diurnal pattern was observed in Hg(0) in
air concentrations, suggesting solar
radiation as the primary driver of Hg(0)
concentrations in air. Solar radiation has
been found to increase stomatal
conductance (the stomata open and
release accumulated mercury vapor from
the intercellular space) and to promote the
photoreduction of deposited Hg(II) to Hg(0)
[(Bash, Miller, Meyer, & Bresnahan, 2004;
Steve E Lindberg, Dong, & Meyers, 2002)]
Grey Line- Temperature Black Line- Hg(0) Concentrations
Nevertheless, relative humidity is also
related with stomatal conductance. As the
percentage of humidity decreases, the
atmospheric Hg(0) concentrations increase,
indicating a relation between leaf water
potential, which decreases stomata
conductance, and therefore decrease Hg(0)
concentrations emission from leaf surfaces
[(Converse, Riscassi, & Scanlon, 2010;
Elfving & Kaufmann, 1972; Wang, Lin, &
Feng, 2014)]. Hence, relative humidity is
also a primary driver of Hg(0)
concentrations in air for this site.
Furthermore, air temperature for this site is
highly positively correlated with solar
radiation (Pearson correlation coefficient =
0.65, p-value <0.001, n=789) and
negatively correlated with relative humidity
(Pearson correlation coefficient = -0.90, p-
value <0.001, n=789). Also, relative
humidity presents a strong negative
correlation with solar radiation (Pearson
correlation factor of -0.76, p-value <0.001
and n=773), and as such, it is not clear
which mechanism (photo-reduction or
stomatal opening) has more impact in the
measured concentrations.
The correlations found above are due to the
fact that, Hg(0) in vegetation is primarily
exchanged through stomatal processes
and transpiration of water, with this
processes depending upon environmental
conditions, [(Hanson, Lindberg, & Tabberer,
1995; S.E. Lindberg, Meyers, Taylor Jr,
Turner, & Schroeder, 1992)].
In addition, other studies have implicated
that photo-reduction reactions in natural
waters as well as in soils and surface
sediments as being primary producers of
elemental mercury, additionally to microbial
reduction processes with temperature, that
may have contributed to the increase
concentrations observed in air and the
correlation with radiation [(Pannu, Siciliano,
& O’Driscoll, 2014; Qureshi, O’Driscoll,
MacLeod, Neuhold, & Hungerbühler,
2010)]. The specific mechanisms at this site
are outside the scope of this study.
Moreover, in order to further investigate the
relationship between wind speed and Hg(0)
in air concentrations, the values for wind
speed were grouped (0-1 m s-1
, 1-2 m s-1
,
2-3 m s-1
, etc.) in classes. For each class of
the grouped wind speeds, the standard
deviations of Hg(0) concentrations were
calculated, in order to study the variance of
vegetation-air Hg(0) fluxes and
concentrations for each wind speed class.
Still, no significant correlation was found for
concentrations (Pearson Correlation value
0.64, p-value=0.17, n=6).
Table 1- Wind direction and Hg(0) concentrations measured
Cardinal
Direction Degree
Average
atmospheric Hg(0)
concentrations
Maximum
atmospheric Hg(0)
concentrations
Minimum
atmospheric Hg(0)
concentrations
NNE 22.50 1.36±0.06 1.45 1.33
NE 45 1.47±0.02 1.27 1.24
ENE 67.50 1.71±0.07 1.76 1.64
SW 225 2.05±0.24 2.43 1.68
WSW 247.5 2.02±0.33 3.53 1.47
W 270 1.78±0.32 3.27 1.30
WNW 292.50 2.02±0.57 3.48 1.30
NW 315 1.62±0.45 3.47 1.18
NNW 337.5 1.80±0.53 3.44 1.22
N 0 (360) 1.60±0.31 2.02 1.32
0 2 4 6 8 10 12 14 16 18 20
0
5
10
15
20
25
12
:45
1
6:3
0
20
:00
2
3:3
0
3:0
0
6:3
0
10
:00
1
3:3
0
17
:00
2
0:3
0
0:0
0
3:3
0
7:0
0
10
:30
1
4:0
0
17
:30
2
1:0
0
0:3
0
4:0
0
7:3
0
20
:15
2
3:4
5
3:1
5
6:4
5
10
:15
1
3:4
5
Hg(
0)
Co
nce
ntr
atio
ns
(ng
m-3
)
Tem
pe
ratu
re (
° C
)
Time
0
5
10
15
20
0 200 400 600 800
1000 1200
12
:45
16
:40
20
:20
0:0
0
3:4
0
7:2
0
11
:00
14
:40
18
:20
22
:00
1:4
0
5:2
0
9:0
0
12
:40
16
:20
20
:00
23
:40
3:2
0
7:0
0
19
:55
23
:35
3:1
5
6:5
5
10
:35
14
:15
Hg(
0)
Co
nce
ntr
atio
ns
(ng
m-3
)
Sola
r R
adia
tio
n (
W m
−2)
Time
Regarding wind directions and atmospheric
Hg(0) concentrations, present in Table 1, it
was observed that 99% of the measured
concentrations are between the winds SW-
N directions (225°- 360°). The remaining
1% present in other directions could affect
the data if the values were anomalous, but
in this case, since their average is only
slightly lower, they do not significantly
interfere (with these concentrations the
average is 1.81 0.49 and without is
1.81 0.19). Therefore, the hypothesis of
inputs of Hg(0) from the vicinity cannot be
assessed since there is not enough
variability in the data.
3.3. Atmospheric Mercury
Concentrations for Site 2
The median concentrations in site 2 were
3.31 2.03 ng m-3
(n= 1078), whilst the
maximum value registered was 18.15 ng m-
3 and a minimum of 1.08 ng m
-3.
This distribution was characterized by
significant variations throughout the
sampling campaign, as one can observe by
the value of the standard deviation. The
Hg(0) concentrations are in good
agreement with the average ambient air
Hg(0) concentrations for industry sites,
which are usually between 0.5-20 ng m-3
(World Health Organization , 2000 ).
Nevertheless, the measured concentrations
present a much wider range when
compared with the background site 1,
presenting peaks of very high Hg(0) in air
concentrations during night, which suggests
that photoreduction and solar radiation
driven processes are less of a factor at this
site and, suggesting, that inputs of gaseous
mercury may be originating from the
vicinity.
Grey Line- Temperature Black Line- Hg(0) Concentrations
Figure 3- Atmospheric Hg(0) concentrations and meteorological variables for site 2, respectively,
solar radiation, wind speed, respectively solar radiation, temperature.
3.3.2. Patterns in atmospheric mercury
concentrations with meteorological
variables for Site 2
The results for the Hg(0) concentrations are
presented in Figure 3. The concentrations
measured present a weak positive
correlation for temperature and relative
humidity (respectively, a Pearson
correlation coefficient = 0.08, p-value
<0.001, n=1078 for temperature and,
Pearson correlation coefficient = 0.25, p-
value <0.001, n=1078). Regarding solar
radiation and wind speed, a weak negative
correlation was found (respectively, a
Pearson correlation factor of -0.26, p-value
<0.001 and n=1078), Pearson correlation
coefficient = -0.20, p-value <0.001,
n=1078).
These anomalous correlations were found
in other studies. For example, the fact that
the increase Hg(0) in air concentrations
does not follow a diurnal pattern with
temperature has been reported on the
Penghu Islands, near Tawain, China. In that
study, total gaseous mercury was
measured during one year, and it was
found that the concentrations of
atmospheric Hg(0) were influenced by
mercury-polluted air masses transported
from remote areas or local stationary
combustion and mobile sources (Jen,
2014).
In addition, in Nevada, United States of
America, atmospheric mercury speciation
was measured for 11 weeks (Weiss-
Penzias, Gustin, & Lyman, 2009) and it was
found that long-range transport of reactive
gaseous mercury from the free troposphere
dominated many of the patterns observed.
All of these results points to the effect of an
input of mercury from the vicinity influencing
the atmospheric Hg(0) concentrations and
flux.
In relation to solar radiation, the measured
atmospheric Hg(0) concentrations also do
not exhibit a diurnal pattern with solar
radiation, again suggesting a factor other
than solar radiation driving air
concentrations of Hg(0).
As for wind speed, the same correlation
was saw by Weiss-Penzias, who observed
that, when the variability of the wind speed
decreases, the measured concentrations
0
4
8
12
16
20
0
1
2
3
4
5
12
:45
16
:30
20
:00
23
:30
3:0
0
6:3
0
10
:00
13
:30
17
:00
20
:30
0:0
0
3:3
0
7:0
0
10
:30
14
:00
17
:30
21
:00
0:3
0
4:0
0
7:3
0
20
:15
23
:45
3:1
5
6:4
5
10
:15
13
:45
Hg(
0)
Co
nce
ntr
aio
ns
(ng
m-3
)
Win
d S
pe
ed
(m
s-1
)
Time
0
5
10
15
20
0
20
40
60
80
12
:45
1
5:4
0
18
:50
2
1:4
5
0:4
0
3:3
5
6:3
0
9:2
5
12
:20
1
5:1
5
18
:10
2
1:0
5
0:0
0
2:5
5
5:5
0
8:4
5
11
:40
1
4:3
5
17
:30
2
0:2
5
23
:20
2
:15
5
:10
8
:05
2
0:1
5
23
:10
2
:05
5
:00
7
:55
1
0:5
0
13
:45
Hg(
0)
Co
nce
ntr
atio
ns
(ng
m-3
)
Re
lati
ve H
um
idit
y (%
)
Time
Grey Line- Wind Speed Black Line- Hg(0) Concentrations
build, showing that they concentrate with
low wind speed and therefore diminish with
high wind speeds.
Lastly, Xu monitored atmospheric Hg(0), in
Windsor, Canada, from 2007 to 2011, in
order to investigate the temporal variability
of Hg(0). Over the five years the average
concentrations were 2.0 ± 1.3 ng m-3
, taken
with an Tekran® 2537A also. The sampling
site was located on the University of
Windsor, with the study suggesting that
10% of the atmospheric Hg(0) in Windsor
was attributable to emissions from industrial
sectors in the region, with temporal patterns
affected by anthropogenic and surface
emissions, as well as atmospheric mixing
and chemistry.
Similarly to site 1, in order to further
investigate the relationship between wind
speed and atmospheric Hg(0) fluxes and
concentrations values, the values for wind
speed were divided in classes (0-1 m s-1
, 1-
2 m s-1
, 2-3 m s-1
, etc.). For each class of
the grouped wind speeds, the standard
deviations of Hg(0) flux and concentrations
were calculated, in order to study the
variance of vegetation-air Hg(0) fluxes and
concentrations with wind speed. Still, no
significant correlation was found for both
fluxes (Pearson Correlation value -0.83, p-
value=0.04, n=6) and concentrations
(Pearson Correlation value 0.34, p-value=
0.51, n=6).
Finally, in relation to wind direction and the
measured concentrations, presented in
Table 2, of the total atmospheric Hg(0)
concentrations measured, 60% of these are
between the wind W-N directions (270° -
360°), in which the directions W-WNW
present the highest average and maximum
concentrations measured.
This range of wind directions points to the
Solvay complex, suggesting that the input
of Hg(0) is from that direction, which may
explain the occurring peaks.
In order to confirm this result, the coefficient
of variation (the standard deviation divided
by the arithmetic mean) was calculated.
This coefficient often indicates the influence
of local sources compared to regional
background contribution, since
contributions from background sources are
generally less variable than contributions
from local sources (Han et al., 2014). The
coefficient of variation found for the
industrial site (Site 2) was 0.62, and 0.27
for the background site (Site 1).
Han reported a coefficient of variation for
total gaseous mercury of 0.79 and 0.69 in in
Seoul and Chuncheon, respectively,
suggesting that local sources impacted the
total gaseous mercury variation, and to a
greater extent in Seoul than in Chuncheon.
Hence, we suggest that the coefficient
values differences are due to local sources,
which have impacted the atmospheric
Hg(0) concentrations variation in Site 2.
Table 2- Wind direction and Hg(0) concentrations measured
Cardinal
Direction
Degree
(°)
Average
atmospheric Hg(0)
concentrations
Maximum
atmospheric Hg(0)
concentrations
Minimum
atmospheric Hg(0)
concentrations
NNE 22.50 2.34±1.34 8.761 1.16
NE 45 1.56±0.31 2.66 1.084
ENE 67.50 1.71±0.27 2.733 1.083
E 90 1.91±0.2 2.17 1.478
ESE 112.50 1.99±0.48 2.90 1.23
SE 135 1.87±0.29 2.28 1.36
Cardinal
Direction
Degree
(°)
Average
atmospheric Hg(0)
concentrations
Maximum
atmospheric Hg(0)
concentrations
Minimum
atmospheric Hg(0)
concentrations
SSE 157.50 2.07±0.40 2.79 1.20
S 180 1.80±0.28 2.37 1.34
SSW 202.50 2.81±0.91 6.38 1.39
SW 225 3.29±0.92 7.82 2.01
WSW 247.5 3.4±0.95 5.3 2.10
W 270 5.0±2.67 15.32 1.74
WNW 292.50 5.2±2.48 16.6 1.84
NW 315 3.37±1.20 12.19 1.68
NNW 337.5 2.93±1.15 7.36 1.22
N 0 (360) 2.33±0.86 5.20 1.38
4. Atmospheric Hg(0)
concentrations and vegetation-air fluxes
for Sarcocornia fruticosa and Halimione
portulacoides
In order to visualize the relative amounts of
vegetation-air fluxes and atmospheric Hg(0)
concentrations on site, for each plant
species it was plotted the respective values
on the table below, Table 3:
Table 3- Averages and standard deviations obtained for H. portulacoides and S. fruticosa regarding Hg(0) vegetation-
airfluxes and atmospheric Hg(0) concentrations for Site 1.
S. fruticosa
H. portulacoides
Hg(0) vegetation-air fluxes
Average 0.04 0.03
Standard Deviation
0.44 0.45
S. fruticosa
H. portulacoides
Atmospheric Hg(0) concentrations
Average 1.78 1.83
Standard Deviation
0.37 0.52
From the following table, it is possible to
observe that, H. portulacoides present
values of Hg(0) flux and air Hg
concentrations, on average, alike the
species S. fruticosa, with a similar standard
deviation.
For the background site (Site 1), no major
differences were observed in the behavior
of these two species regarding fluxes and
concentrations of atmospheric Hg(0).
Regarding their behavior for Site 2, the
following results were obtained, Table 4:
Table 4- Averages and standard deviations
obtained for H. portulacoides and S.
fruticosa regarding Hg(0) vegetation-air
fluxes (ng m-2
hr-1
) and atmospheric Hg(0)
concentrations (ng m-3
) for Site 2.
H. portulacoides
H. portulacoides
S. fruticosa
H. portulacoides
Hg(0) vegetation-air fluxes
Mean 6.66 0.27 0.25 6.08E-
06
Standard Deviation
6.92 4.22 3.43 3.79E-
04
Atmospheric Hg(0) concentrations
Mean 3.68 2.73 3.82 3.07
Standard Deviation
1.47 1.61 2.34 1.83
The measured concentrations and
respective fluxes for these species present
an erratic behavior (higher standard
deviation values), probably due to the
possible input of Hg from the surrounding
industrial area and chloralkali plant.
The first H. portulacoides measured shows
high values of flux but the last H.
portulacoides measured shows low values;
the S. fruticosa specie shows a pattern
similar to the second H. portulacoides
measured, so no significant differences are
observed with the given variations.
Regarding the atmospheric Hg(0)
concentrations, the species Sarcocornia
fruticosa presents slightly higher values
(3.82 ng m-3
) for Hg(0) concentrations in air
near the species, when compared with the
average values for Halimione portulacoides
of 3.16 ng m-3
. Still, these values are too
low to windraw any relation.
5. Conclusions
As stated in 3.1, no significant correlations
were found between vegetation mercury
flux and any of the studied variables, for
site 1 and 2. For the first site, the calculated
fluxes were too low, near detection limit,
therefore, it is likely that other natural
volatilization sources were largely
responsible for the increased air
concentrations.
For site 2, inputs of atmospheric mercury
from the vicinity caused a wide dispersion
of concentrations, interfering with the
calculated fluxes.
A very strong correlation was found
between atmospheric Hg(0) concentrations
and solar radiation at the background site,
identifying this variable as one of the
primary drivers of Hg(0) concentrations in
air. Other variables related to solar radiation
were also significantly correlated with Hg(0)
in air such as air temperature and relative
humidity. No important relation was found
between wind speed and the measured
concentrations at the background site.
The temporal examination of mercury
vegetation flux and Hg(0) concentrations in
air, showed that high variability and large
mercury concentrations were measurable
during the dark hours. This suggested that
solar radiation was not the primary driver of
mercury release at the industrial site. It was
found that wind directions were responsible
for the dispersion of values.
We hypothesize that this site is primarily
affected by local atmospheric Hg emissions
from the W-WNW directions. The large
Hg(0) background in air made
measurements of flux from vegetation
impossible. One important remark is that
these directions point to the Solvay
industrial complex, which during the
sampling time was being dismantled. It is
not clear why the concentrations
consistently rose dramatically at night.
Regarding the Hg(0) vegetation-air fluxes
for Sarcocornia fruticosa and Halimione
portulacoides, no major differences in
trends were observed between plant
species for site 1, and, the differences
observed for site 2 with flux, may be due to
large background concentrations from the
surrounding area.
Although the sampled data was limited, the
information disseminated warrants further
investigation, especially for site 2 in order to
verify the hypothesis that this site is being
affected by local atmospheric Hg
emissions. Also, as future work, it is
proposed to hold a similar study elsewhere
in the estuary, where "hot spots" of mercury
are reported, in order to compare with the results obtained in this study.
6. Acknowledgements
The research for this study was made possible by the project PLANTA – “Efeitos das plantas de
Sapal na metilação, transporte e volatilização para a atmosfera de mercúrio” (Ref: PTDC/AAC-
AMB/115798/2009) funded by the Fundação para a Ciência e Tecnologia. This work was also
possible by the financial support of NSERC Discovery Grant and Canada Research Chairs
Program, Canada.
7. References
Bash, J. O., Miller, D. R., Meyer, T. H., & Bresnahan, P. a. (2004). Northeast United States and Southeast Canada natural mercury emissions estimated with a surface emission model. Atmospheric Environment, 38(33), 5683–5692. doi:10.1016/j.atmosenv.2004.05.058
Black, G. J., Campbell, D. B., & Harmon, J. K. (2010). Radar measurements of Mercury’s north pole at 70cm wavelength. Icarus, 209(1), 224–229. doi:10.1016/j.icarus.2009.10.009
Canário, J., Branco, V., & Vale, C. (2007). Seasonal variation of monomethylmercury concentrations in surface sediments of the Tagus Estuary (Portugal). Environmental Pollution (Barking, Essex : 1987), 148(1), 380–3. doi:10.1016/j.envpol.2006.11.023
Canário, J., & Vale, C. (2004). Rapid release of mercury from intertidal sediments exposed to solarradiation: a field experiment. Environ Sci Technol. 2004 Jul 15;38(14):3901-7.
Canário, J., Vale, C., & Caetano, M. (2005). Distribution of monomethylmercury and mercury in surface sediments of the Tagus Estuary (Portugal). Baseline / Marine Pollution Bulletin 50 (2005) 1121–1145.
Canário, J., Vale, C., Poissant, L., Nogueira, M., Pilote, M., & Branco, V. (2010). Mercury in sediments and vegetation in a moderately contaminated salt marsh (Tagus Estuary, Portugal). Journal of Environmental Sciences, 22(8), 1151–1157. doi:10.1016/S1001-0742(09)60231-X
Converse, a. D., Riscassi, a. L., & Scanlon, T. M. (2010). Seasonal variability in gaseous mercury fluxes measured in a high-elevation meadow. Atmospheric Environment, 44(18), 2176–2185. doi:10.1016/j.atmosenv.2010.03.024
Elfving, D. ., & Kaufmann, M. R. (1972). Interpreting Leaf Water Potential Measurements with a Model of the Soil-Plant-Atmosphere Continum. Physiol.Plant. 27: 161-168.1972.
Figueres, G., Martin, J. M., Meybeck, M., & Seyler, P. (1985). A comparative study of mercury contamination in the Tagus estuary (Portugal) and major French estuaries (Gironde, Loire, Rhône). . Estuar. Coast. Shelf Sci. 20, 183-203.
Han, Y.-J., Kim, J.-E., Kim, P.-R., Kim, W.-J., Yi, S.-M., Seo, Y.-S., & Kim, S.-H. (2014). General trends of atmospheric mercury concentrations in urban and rural areas in Korea and characteristics of high-concentration events. Atmospheric Environment, 94, 754–764. doi:10.1016/j.atmosenv.2014.06.002
Hanson, P. J., Lindberg, S. E., & Tabberer, T. A. (1995). Foliar exchange of mercury vapor: evidence for a compensation point. Water, Air & Soil Pollution;Feb1995, Vol. 80 Issue 1-4, p373.
Jen, Y.-H. (2014). Field Measurement of Total Gaseous Mercury and Its Correlation with Meteorological Parameters and Criteria Air Pollutants at a Coastal Site of the Penghu Islands. Aerosol and Air Quality Research, 364–375. doi:10.4209/aaqr.2013.03.0073
Leco. (2002). Advanced Mercury Analyzer- AMA 254.
Lindberg, S. E., Dong, W., & Meyers, T. (2002). Transpiration of gaseous elemental mercury through vegetation in a subtropical wetland in Florida, 36(2002), 5207–5219.
Lindberg, S. E., Meyers, T. P., Taylor Jr, G. ., Turner, R. R., & Schroeder, W. H. (1992). Atmosphere-surface exchange of mercury in a forest: results of modeling and gradient approaches. Journal of Geophysical Research: Atmospheres (1984–2012) Volume 97, Issue D2, Pages 2519–2528, 20 February 1992.
Lodenius, M. (1998). Dry and wet deposition of mercury near a chloralkali plant. The Science of the Total Environment 213 1998 53 Ž . ]56.
Lodenius, M., Tulisalo, E., & Soltanpour-Gargari, a. (2003). Exchange of mercury between atmosphere and vegetation under contaminated conditions. The Science of the Total Environment, 304(1-3), 169–74. doi:10.1016/S0048-9697(02)00566-1
Pannu, R., Siciliano, S. D., & O’Driscoll, N. J. (2014). Quantifying the effects of soil temperature, moisture and sterilization on elemental mercury formation in boreal soils. Environmental Pollution (Barking, Essex : 1987), 193, 138–46. doi:10.1016/j.envpol.2014.06.023
Poissant, L., Pilote, M., Yumvihoze, E., & Lean, D. (2008). Mercury concentrations and foliage/atmosphere fluxes in a maple forest ecosystem in Québec, Canada. Journal of Geophysical Research, 113(D10), D10307. doi:10.1029/2007JD009510
Qureshi, A., MacLeod, M., Scheringer, M., & Hungerbu, K. (2009). Mercury cycling and species mass balances in four North in four american lakes. Environ. Pollut., 157, 452–462, doi:10.1016/j.envpol.2008.09.023.
Qureshi, A., O’Driscoll, N. J., MacLeod, M., Neuhold, Y., & Hungerbühler, K. (2010). Diurnal photoreactions of mercury in surface ocean water: quantitative rate kinetics, reaction pathways and a predictive model. Environmental Science and Technology.44 (2): 644–649.
Rea, A. W., Lindberg, S. E., Scherbatskoy, T., & Keeler, K. G. (2002). Mercury Accumulation in Foliage over Time in Two Northern Mixed-Hardwood Forests. Environmental Science and Technology.44 (2): 644–649.
Tekran. (2001). Tekran Model 1130 Mercury Speciation Unit and Model.
UNEP. (2013). Global Mercury Assessment. UNEP Chemicals Branch, Geneva, Switzerland.
Wang, X., Lin, C.-J., & Feng, X. (2014). Sensitivity analysis of an updated bidirectional air–surface exchange model for elemental mercury vapor. Atmospheric Chemistry and Physics, 14(12), 6273–6287. doi:10.5194/acp-14-6273-2014
Weiss-Penzias, P., Gustin, M. S., & Lyman, S. N. (2009). Observations of speciated atmospheric mercury at three sites in Nevada: Evidence for a free tropospheric source of reactive gaseous mercury. Journal of Geophysical Research, 114(D14), D14302. doi:10.1029/2008JD011607
World Health Organization. (2000). Air Quality Guidelines – Second Edition. WHO Regional Publications, European Series, No. 91.
Xu, X., Akhtar, U., Clark, K., & Wang, X. (2014). Temporal Variability of Atmospheric Total Gaseous Mercury in Windsor, ON, Canada. Atmosphere, 5(3), 536–556. doi:10.3390/atmos5030536
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