Atmospheric mercury vegetation/air fluxes and ... · Atmospheric mercury vegetation/air fluxes and concentrations in contaminated sites of the Tagus Estuary, Portugal Sara Justinoa*,

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

*[email protected]

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

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:05

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:05

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:05

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:05

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:00

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:25

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: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

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:05

17

:35

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:05

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:35

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:40

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5:1

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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.

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