Abiotic methylation of inorganic

mercury in natural waters

Method development for determination of

monomethylmercury in natural waters by GC-ICP-MS

Thu-Hoai Nguyen

Student

Master Thesis 30 ECTS

Supervisors: Erik Bjorn, Aleksandra Skrobonja

Examiner: Lars Backman

I

Abstract

Methylmercury neurotoxicity poses a great risk to the environment and human health. To

understand the transformation and transfer of methylmercury, it is important to determine the

exact concentration and methylation/demethylation rates. Advanced analytical techniques, such

as Gas Chromatography Inductively Coupled Plasma Mass Spectrometry have achieved good

quantifications down to femtomole levels of methylmercury, but it is still facing a great

challenge in natural water samples, with low concentration and weak bacterial activities. Since

biotic methylation of inorganic mercury in waters are low, a small percentage of abiotic

(artificial) methylation will result in overestimation of methylmercury concentration, we must

examine the origin of artifacts, as well as devise feasible solutions. In this project, we

investigated process of these artifact formations and found 0.3%-1.24% abiotic methylation of

inorganic mercury in artificial samples and 0.54%-1.25% in natural waters. These artifacts can

be credited to storage in organic-rich matrix. Some possible abiotic pathways and organic

matter-mercury interactions were reviewed, and solutions were discussed.

II

III

List of abbreviations

MMHg/MeHg Monomethyl mercury

DMeHg Dimethyl mercury

Hg Mercury

HCl Hydrochloric Acid

NaOH Sodium hydroxide

STEB Sodium tetraethyl borate

GC Gas chromatography

ICP MS Inductively Coupled Plasma Mass Spectrometry

TD Thermal desorption

IDA Isotope dilution analysis

RIDA Reverse isotope dilution analysis

DOM Dissolved organic matter

DOC Dissolved organic carbon

OM Organic matter

Author contribution

In this material, I proposed the hypothesis, designed experiment, performed onsite

sampling, calculated and analyzed based on provided templates, with the mentoring and

advice of my supervisors. Experimental data of natural waters by other author were

mention specifically.

IV

V

Content

Abstract .......................................................................................................................... I Author contribution ...................................................................................................... III Content .......................................................................................................................... V

1. Introduction ................................................................................................................ 1 2. Popular scientific summary including social and ethical aspect ................................ 3

2.1 Social and ethical aspects ..................................................................................... 3 2.2 Popular scientific summary.................................................................................. 3

3. Experimental .............................................................................................................. 3

3.1 Materials and chemicals ....................................................................................... 3 3.1.1 Field sampling ............................................................................................... 3 3.1.2 Stock and standard solutions ......................................................................... 4

3.1.3 Reagents and other chemicals ....................................................................... 4 3.2 Instruments ........................................................................................................... 4 3.3 Methods................................................................................................................ 4 3.4 Quality control and calculation of uncertainties .................................................. 5

3.4.1 Mass bias ....................................................................................................... 5 3.4.2 Identification of artifact signal ...................................................................... 5

4. Results and Discussion .............................................................................................. 6 4.1 Mili-Q sample ...................................................................................................... 6

4.2 DOM artificial matrix .......................................................................................... 6 4.3 Natural water sample ........................................................................................... 9

4.3.1 Stream water (KSN) ...................................................................................... 9

4.3.2 Brackish water (Holmsund) .......................................................................... 9 4.4 The significance of artifactual methylation by DOM .......................................... 9

4.5 Interaction between DOM and Hg ..................................................................... 10 4.6 Minimizing artifactual methylation ................................................................... 11

5. Conclusions .............................................................................................................. 11 6. Outlook .................................................................................................................... 11

Acknowledgment ......................................................................................................... 11 References .................................................................................................................... 12 Appendix I: Matrix deconvolution method to calculate concentrations of

methylmercury ............................................................................................................. 14

VI

1

1. Introduction

Mercury (Hg) is a highly toxic trace metal pollutant and omnipresent in environmental

systems. Mercury species can be emitted from natural sources (forest fire, volcanoes,

erosion of cinnabar ore, etc.), or released as industrial waste discharge1. Microbial

activity can also transform Hg between different chemical forms1. The organic form,

methylmercury (MeHg), is especially hazardous, as it is neurotoxic and capable of

bioaccumulation and biomagnification in the food chains, starting from bacteria uptake

to human consumption2. Hence, it is important to determine the exact concentration of

MeHg to understand the formation, transportation, and distribution of mercury in the Hg

cycle. Determination of total Hg is insufficient, as each Hg species will have different

fate and transport mechanism in the system. By measuring the exact concentration of

MeHg, we can understand the process of accumulation and biomagnification in Hg

cycle, formation and transformation between Hg species, as well as natural systems

formation/degradation. MeHg is the most toxic form, hence, it is also crucial to predict

how climate change affect MeHg in the nature cycle and make risk assessments on

MeHg exposure.

In most aquatic ecosystems, the main source of MeHg is methylation of inorganic Hg

(in-situ production), as compared to input from runoff water or atmospheric deposition3.

Net production of MeHg occurs via two reversible processes: mercury methylation and

demethylation. Many scientists assume concentration changes during Hg species

transformation follow pseudo first-order reversible kinetics model and can be express as

following equation2,4.

𝑑[𝑀𝑒𝐻𝑔]

𝑑𝑡= 𝑘𝑚[𝐻𝑔]𝐼𝐼 − 𝑘𝑑[𝑀𝑒𝐻𝑔] (1)

𝑑[𝐻𝑔]𝐼𝐼

𝑑𝑡= −𝑘𝑚[𝐻𝑔]𝐼𝐼 + 𝑘𝑑[𝑀𝑒𝐻𝑔] (2)

where 𝑘𝑚= methylation rate constant (day-1 or d-1), 𝑘𝑑= demethylation rate constant,

[𝐻𝑔]𝐼𝐼= concentration of inorganic Hg, [𝑀𝑒𝐻𝑔]=concentration of MeHg.

The methylation mechanism can be explained via two pathways: biotic and abiotic. The

former mechanism depends on enzymatic processes of anaerobic bacteria, namely

sulfate-reducing (SRB) and iron-reducing (IRB) bacteria3,5. The abiotic sources are not

fully understood, but it can be attributed to the transfer of methyl group donor in organic-

rich environments in the presence of sulfur or catalytic metals6,7. pH, temperature, the

presence of sulfur groups and organic content are some factors which affect

methylation/demethylation.

Improvements in analytical techniques have been made in mercury speciation analysis

to aid our understanding of the biogeochemical cycling of Hg. However, determination

of MeHg is challenging because of non-quantitative recoveries and the possibility of

artifact formation6,8,9 and transformations of methylmercury during the sample-

preparation and separation steps1,10,11.

Among these analytical methods, isotope dilution analysis (IDA) is a powerful method

in use with GC ICP-MS allowing quantification to femtomolar concentrations of

MeHg12–14. The basic principle of isotope dilution analysis is illustrated in Figure. 1.

2

Figure i. Schematic illustration of the principles of isotope dilution analysis for two isotopes

The sample contains the analyte (MeHg) with its natural isotope composition. To the

sample, we add a standard, largely enriched in one Hg isotope, which causes a shift in

the isotope pattern for MeHg in the mix. By recording the signal count, we can calculate

the ratio of two isotopes in the mix, then the concentration of native MeHg15.

For more than two isotopes, we must resolve each component’s signal contribution to

the measured isotope pattern. This is accomplished by a mathematical deconvolution

calculation of the signals. The isotope intensity measured by GC-ICPMS is a convolute

of (i) amounts of tracer and ambient Hg (mole) and (ii) isotopic composition of tracer

and ambient Hg (ratio). As a result, the deconvoluted signal is the add tracer’s

contribution to the overall convolute signal. More on convoluted calculation is explained

in Appendix I.

The main advantages of IDA are the ability to compensate for analyte losses and

degradation, matrix components which affect atomization, ionization efficiencies, and

space-charge effects. However, the formation of analyte species after equilibration is not

often corrected. In natural water samples, the concentrations of MeHg are much lower

than those in sediment and artificial methylation can result in serious overestimation8,16.

In soil sediment, methylation rate of inorganic Hg is quite high, for example, Jonsson et

al (2012) reported the first-order rate constants for Hg (II) methylation to be 0.12 ± 0.014

day -1 17. Meanwhile, in water, a rate constant as low as 0.006 ± 0.002 day -1 was recorded 18. These methylations were attributed mainly to biotic methylation, while abiotic

methylation is often ignored or considered as artifact. In this project, we defined artifact

(or artificial methylation) is an unintended methylation, which does not occur in the

natural environment but caused by the handling of samples (during sample preparation

or usage of reagent). This term is used with consistency to existing literature in mercury

analysis, as to avoid confusion and fabrication of new term.

3

The major objectives of this project are (1) to investigate possible processes for artifact

MeHg formation in different natural water samples (stream water, brackish water, and

seawater) and (2) to develop methods to minimalize artifact.

2. Popular scientific summary including social and ethical

aspect

2.1 Social and ethical aspects

From 1956-2001, more than 2000 people were recognized with the Minamata disease,

signified by muscles numbness, loss of vision, damage to hearing and speech, and in

extreme cases, paralysis, insanity and eventually, death. The identified culprit is the

neurotoxic methylmercury, discharged from Chisso Corporation as a by-product of

chemical production 34. In 2013, United Nation Minamata Convention on Mercury was

signed, “recognizing that mercury is a chemical of global concern” 35. This thesis project

was done as a small contribution to expand our understanding of methylmercury in

aquatic systems, which could have an impact on human health and environment.

Our project does not involve testing on animals and human being. Risk assessment and

lab safety was carried out.

2.2 Popular scientific summary

Methylmercury (MeHg) poses a great risk to the environment and human health;

therefore, it is crucial to study its behavior and characteristic in different environments.

The concentration of inorganic mercury (Hg) and MeHg are determined by two

reversible processes: methylation and demethylation1. To build an accurate model of

MeHg transformation and transportation, we must determine the exact MeHg

concentration, which is more challenging in aquatic samples than in sediment, with

lower concentrations and less active bacteria culture. Advanced analytical techniques,

such as Gas Chromatography Inductively Coupled Plasma Mass Spectrometry (GC ICP-

MS) allows us to analyze to femtomolar (10-15) level, however, traces of artifact are still

found and resulting in serious overestimation12. By using a stepwise approach, we

identified the source of artifact to be abiotic (i.e. without bacteria) methylation in the

organic-rich matrix during storage. Each type of water samples yields different artifact

methylation level. The challenge remains in how to reduce the artifact and improve the

analytical method.

3. Experimental

3.1 Materials and chemicals

3.1.1 Field sampling

We sampled stream water at a boreal site named Kroksjon (KSN) (63°57′8″N

20°38′11″E) in northern Sweden and brackish water at Holmsund shore (63°41′22″N

20°20′39″E). Azlon HDPE type 1 and 2 liters were used. Collected water was stored at

-4oC within 1 hour after sampling.

pH and temperature were recorded at the time of sampling, while DOC values were

estimated from previous studies by L. Nguyen 19 et al and A.L. Soerensen 20

4

Table 1: Characteristic of natural water samples

pH Temperature (oC) DOC (mg/l)

Kroksjon 3.5-4 -0.7 49

Holmsund 5 0.2 20

All samples were filtered with 0.45 µm immediately before purging to prevent

blockage and/or contamination of the system.

3.1.2 Stock and standard solutions

Isotope standards (Natural MeHg, Me200Hg, 199Hg, and 198Hg) were prepared freshly

from stock solution with concentrations of 16.29 mM, 40.18 uM, 1.08 mM and 2.08

mM, respectively.

3.1.3 Reagents and other chemicals

All solutions and standards were prepared with Mili-Q water (Milli-Q Advantage A10

Ultrapure Water Purification System, Merck Millipore)

Artificial matrix was created using Mili-Q water and a reference sample, Suwannee

River natural organic matter (SRNOM) 201N 2R101N, with DOC concentration

approximately 50 mg/l.

Acetate buffer 2M was prepared by dissolving 15.4 g of CH3COONH4.3H2O (AnalaR

NORMAPUR >99.7%), to 100 ml Milli-Q water, adjust pH to 5 using concentrated HCl.

Sodium hydroxide was prepared at the beginning of each week, by taking 40g of solid

NaOH (AnalaR NORMAPUR >99%) and dissolving to 50 ml Mili-Q.

STEB working solution 1% (w/w) was prepared by taking 2 ml of STEB stock solution

20% (w/w) diluted into 38 ml deoxygenated Milli-Q water, then split into 3ml vials and

store in a freezer until use.

3.2 Instruments

All measurements were carried out on TD-100 Markes – GC 7890B Agilent – ICP-MS

7700 Agilent

Table 2: Operational parameters of TD GC-ICPMS

Tube thermal desorption Temperature 250oC

Flow path temperature 180oC

Carrier pressure 5 psi

GC – Front inlet Flow pressure 15 psi

Pressure 12 psi

Temperature 200oC

Mode Splitless

GC – Column Carrier gas He

Pressure 12 psi

ICP-MS Isotopes measured 198Hg, 199Hg, 200Hg, 202Hg

Run time 6’45’’

3.3 Methods

Isotope dilution analysis for GC ICP-MS is applicable to fresh water, saline water, and

soil/sediment pore water. The method is based on Lambertsson and Björn, Anal.

Bioanal. Chem. 2004 (380) 871-875 and Munson et al. Limnol. Oceanogr. Methods

2014 (12) 1-9.

5

For fresh and pore water samples, we added 50 - 100 ml water sample, 200 μl acetate

buffer and 100 μl STEB in a purging vessel. pH is adjusted to 5 with NaOH 1M if

necessary. The sample was spiked with targeted isotopes, then was purged with nitrogen

gas and trapped by a Tenax tube for 10-15 minutes. The nitrogen gas flow rate is set to

be around 300 ml/min. For brackish and saline waters, we added an additional 300 μL

2.5% (w/v) ascorbic acid.

After usage, the purging vessel was acid-washed with acid HCl 1%, then dried in the

300oC oven in 3 hours (then around 12 hours cooling to normal room temperature) to

further eliminate possible contamination.

For this project, 198Hg was studied to test whether the artifact formation of

methylmercury is possible under experimental condition. 198Hg2+ + CH3

- CH3 198Hg+

198Hg was spiked into different water samples: Mili-Q, DOM artificial matrix, and

natural waters. DOM and natural water samples were acidified by HCl 1%, then stored

at -4oC in clean fridges from 1 to 5 days. 199Hg was used as a reference for 198Hg, and if

being used, it was always spiked at the time of purging. Me200Hg was always spiked at

the time of purging to determine the concentration of possible Me198Hg and Me199Hg.

Concentrations of Me200Hg should correspond to ambient MeHg and inorganic Hg to

achieve detectable signals. Therefore, we used a range of 50 fM-250 fM for 500 fM 198Hg and 199Hg, a concentration of 10 pM for 160 pM 198Hg.

All concentrations used in this report are the final concentration in purging vessels.

3.4 Quality control and calculation of uncertainties

3.4.1 Mass bias

Mass bias is the ratio between theoretical and actual (instrument-run value) of a mercury

isotope in natural distribution.

𝑀𝑎𝑠𝑠 𝑏𝑖𝑎𝑠 𝑓𝑜𝑟 𝐻𝑔𝑖 =𝑁𝑎𝑡𝑢𝑟𝑎𝑙 𝑎𝑏𝑢𝑛𝑑𝑎𝑛𝑐𝑒 (𝐼𝑈𝑃𝐴𝐶 𝑟𝑒𝑝𝑜𝑟𝑡)

𝐴𝑝𝑝𝑎𝑟𝑒𝑛𝑡 𝑎𝑏𝑢𝑛𝑑𝑎𝑛𝑐𝑒 𝐻𝑔𝑖 (𝑖𝑛𝑠𝑡𝑟𝑢𝑚𝑒𝑛𝑡 − 𝑟𝑢𝑛)(3)

Mass bias was performed weekly on natural MeHg standard. Natural MeHg stock

solution concentration was 16.29 mM and diluted to 50 pM in purging vessel. The mass

bias weekly result is consistent and tends towards numerical values of 1.

We used the following value to correct the instrument signal:

Table 3: Mass bias correction value

198Hg 1.0213 199Hg 1.0363 200Hg 1.0635 202Hg 0.9801

3.4.2 Identification of artifact signal

We outlined several criteria to decide if the signal of MeHg is due to the artifactual

formation of inorganic or is due to instrument noise. These criteria are

- The signal-to-noise ratio should be larger than 3 for a quantitative peak

- The inorganic Hg should give a 4.8% signal contribution to the total measured signal

intensity at the specific isotope mass. This factor was determined based on typically

6

expanded uncertainties in measured signal intensities, and thus an individual LOD was

calculated for each isotope tracer and sample 17.

- The concentration duplicate should not fluctuate around zero to be considered statically

significant

4. Results and Discussion

Our strategy was to start with the simplest samples with fewest experiment steps, then

stepwise add more reagents, more complex matrix and include sample preparation. By

doing this, we can isolate and examine the possible sources of artifact. We started with

Mili-Q water spiked in 198Hg and 200MeHg, then artificial dissolved organic matrix, and

finally various natural samples.

The concentration of artifact Me198Hg and Me199Hg was calculated from Me200Hg

spiked concentration, while the percentage of Hg methylation was calculated by

%𝐻𝑔198 𝑔𝑒𝑡 𝑚𝑒𝑡ℎ𝑦𝑙𝑎𝑡𝑒𝑑 =𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑀𝑒𝐻𝑔198

𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑠𝑝𝑖𝑘𝑒𝑑 𝐻𝑔198 (4)

4.1 Mili-Q sample

Contamination from reagent STEB or previous run can alter isotope ratios and cause

inaccurate results. We monitored possible contamination by running sample blank

routinely and found no detectable MeHg signal.

In Mili-Q sample, we spiked in 198Hg and 200MeHg at the time of purging. After running

two different sets of samples with and without acetate buffer, we did not recognize any

MeHg artifact in either set, based on the criteria listed above. Literature suggests that

methyl group (CH3-) in acetate buffer can induce methylation by forming various

complexes with Hg.21 In a study by Akagi and Takabatake (1973), an efficient

photochemical formation of methylmercury was achieved in a heterogeneous system

containing mercuric acetate and solid mercuric oxide. In the case of methylation from

Hg(CH3COO)n=1–4, Gardfeldt et al (2003) reported apparent rate constant for

methylation of 4.28 ±10-7 and 2.48 ± 10-7 s-1, at pH of 4.9 and 5.1, respectively.

We examined the effect of time on acetate-induced methylation, by varying the purging

time to 5, 30 and 60 minutes. The recommended purging time is 10-20 minutes for

quantitative results14, and it followed accordingly that we have no detectable MeHg

signal in 5-min purging. During longer purging time (up to 60 minutes), we did not find

any trace of MeHg artifact that fulfills the artifact criteria.

From the result of our experimental conditions, we considered that acetate buffer is not

a significant source of methylation after applying the criteria for the MeHg artifact. It

appeared that the purging time is too short and methylation rate via acetate complexes

is too low to have any observable effects.

Meanwhile, there are better signal-to-noise results for samples with buffer. Therefore,

acetate buffer should not be removed from our standard procedure.

4.2 DOM artificial matrix

After preparing DOM 50 mg/l in Mili-Q, we spiked in 198Hg, acidified to 1% HCl and

stored samples at -4 oC. Me200Hg was spiked at the time of purging.

7

We assumed that in the DOM from Suwanee reference material, biotic methylation is

negligible, as bacteria is inactive. Suwanee DOM was prepared by 72-hour freeze-

drying, with temperature decreasing from 120oC to 65oC 22, while anaerobic bacteria

slurry can be sterilized at 65oC for 6 hours23.

Table 4: The artifactual methylation of 198Hg (500 fM) in DOM with different storage time

Without storage 1-day storage 3-day storage

Me198Hg

concentration

Not detectable 2.4 ± 0.7 fM 3.3 ± 0.8 fM

%198Hg get

methylated

N/A 0.30% 0.61%

We noticed that the concentrations no longer fluctuated around zero in 1-day storage

samples, and 3-day storage resulted in all-positive values, with higher methylation

percentagein comparison with DOM-no storage and Mili-Q water, which may imply

abiotic methylation.

To ensure that we observed abiotic methylation, we used another isotope, 199Hg as a

reference. 198Hg was stored in the fridge, while 199Hg was not stored and spiked in at the

time of purging. If abiotic methylation occurs during storage, we expect signals from

artifact Me198Hg and not Me199Hg

Table 5: The artifactual methylation of 198Hg (500 fM) and 199Hg (500 fM) in DOM with and without storage

5-day storage No storage

Me198Hg concentration 1.42 ± 0.6 fM Not detectable

Me199Hg concentration Not detectable Not detectable

%198Hg methylated 0.28% N/A

%199Hg methylated N/A N/A

The result was expected and consistent with the previous. As shown in Table 5, for both

5-day storage and no storage sample, 199Hg showed no sign of methylation while we

found 0.28% methylation of 198Hg after 5-day storage. The result suggests that exposure

to DOM matrix for a period of time cause artifactual methylation of inorganic Hg.

As seen from Figure 2, the relationship between time and artifact methylation is not

linear, as the concentration increased from 1 day to 3 days, then decreased in 5-day

storage. We also noticed that after a week, quantitative signals could not be recorded,

and so they were not expressed in the Figure 2. In incubation experiment to determine

biotic methylation, after a certain time, demethylation rate will surpass methylation,

resulting in a stable or decreasing net MeHg17,24. However, in our DOM artificial matrix,

anaerobic bacteria are assumed to not be active, so it was possible that at low

concentration, artifact MeHg will be degraded over time naturally.

8

Figure ii: Concentration of artificial Me198Hg and %methylation with respect to time

We then increased the concentration of 198Hg in DOM to see if higher concentration will

result in the same artifact methylation. Table 6: The artifactual methylation of 198Hg (2 pM) in DOM

5-day storage in acid

Me198Hg concentration 14 ± 3 fM

Me199Hg concentration Not detectable

%198Hg methylated 1.24%

%199Hg methylated Not detectable

The result with a higher concentration of 198Hg (2 pM) also showed a consistent 198Hg

methylation, both with and without acid storage. The 1.24% methylation is also the

highest value recorded of all samples.

We wanted to study the effect of pH on artifact methylation, but for unacidified samples

at low concentration, the signals were lost after days of storage, as Hg is presumably

hydrolyzed or absorbed into containers.

The only result we got for unacidified samples was at 2 pM for 198Hg. There was

evidence of artifact methylation even without acid, and we can conclude that DOM can

methylate inorganic Hg, abiotically. However, it was unclear in our experiment whether

pH correlates with artifact methylation in DOM matrix, (i.e if higher pH results in higher

artifact methylation, etc.) since storage without acid at lower concentration resulted in

the loss of signal, and we could not draw any conclusion.

Table 7: The artifactual methylation of 198Hg (2 pM) in DOM

Storage without acid

Me198Hg concentration 12 ± 3 fM

Me199Hg concentration N/A

%198Hg methylated 0.59%

%199Hg methylated N/A

2,4

3,3

1,42

0,30%

0,61%

0,28%

0,00%

0,20%

0,40%

0,60%

0,80%

0

0,5

1

1,5

2

2,5

3

3,5

4

1 3 5

%m

eth

ylat

ion

Co

nce

ntr

atio

n o

f M

e1

98 H

g (f

M)

DaysMeHg198 concentration

%Hg198 methylation

9

4.3 Natural water sample

4.3.1 Stream water (KSN)

By spiking only MeHg200 into KSN sample, we determined the concentration of native

MeHg was 2.1 ± 0.3 pM. Therefore, we decided to use a higher concentration of 198Hg

to get better signals, since the high concentration of ambient MeHg affected added

isotopes standards.

Table 8: The methylation of 198Hg (160 pM) in stream water

No storage 1-day storage

Me198Hg concentration Not detectable 2.4 ± 0.5 pM

%198Hg methylated N/A 1.25%

There is no sign of artifact for spiked-in 198Hg at the time of purging, which is consistent

with previous data. The methylation percentage in KSN sample (1.25%) is much higher

than in DOM artificial matrix (0.3%) for 1-day storage. This could be due to the higher

DOM content in KSN samples, biotic methylation, or higher total mercury species

concentration. However, biotic methylation was highly improbable, as water samples

were acidified by 1% HCl, which, theoretically, could stop bacterial activities25.

4.3.2 Brackish water (Holmsund)

Table 9: The methylation of 198Hg (160 pM) in brackish water

No storage 1-day storage in acid

Me198Hg concentration Not fulfill criteria 680 ± 40 fM

%198Hg methylated N/A 0.54%

The methylation percentage of brackish water (0.54%) is lower than those in KSN

(1.25%), which could be explained by lower DOM-content in Holmsund samples.

However, DOM artificial matrix has higher DOM-content, yet lower methylation

percentage in comparing to brackish water. Therefore, we could not draw any direct

relationship between DOM-content and artifact methylation rate. Literature suggests the

presence of sulfates and the availability of organic carbon are important factors affecting

methylation1, hence, it is possible that sulfates content in brackish water is higher than

in DOM artificial matrix. We concluded that matrixes in various natural water samples

yield different abiotic methylation

4.4 The significance of artifactual methylation by DOM Determination of abiotic methylation has been difficult, since sterilization methods by

physical (UV, radiation) or chemical (acid sodium azide, formaldehyde) will change the

properties of matrixes to some extents. However, with our approaches, possible artifact

formation processes have been examined systematically and yielded consistent results.26 The percentage of artifact methylation may appear to be very small (<2%), but it could

cause great overestimations. For instance, in a methylation-demethylation rate studies in

Canadian lakes, Eckley et al (2006) reported 0.11-13.8% of inorganic Hg isotope

methylated per day27. Without considering abiotic methylation contribution, this may

cause systematic errors.

10

4.5 Interaction between DOM and Hg In this section, we review some characteristics of DOM and the interaction between Hg

and DOM. All previous researchers have shown that various agents are possible for

abiotic methylation, which explained our observable MeHg artifact in the analysis.

However, in the scope of this project, we are not concerned with exploring which

specific mechanism applied to which specific samples.

To understand how DOM can methylate inorganic Hg abiotically, we should have an

overview of DOM characterization, as well as how DOM interacts with Hg.

Dissolved organic matter (DOM) is a complex mixture of aromatic and aliphatic

hydrocarbon structures with functional groups, and its molecular weight can be up to

100 000 Dalton28. About 20% of DOM consists of carbohydrates, carboxylic acids,

amino acids, hydrocarbons and other identifiable compounds. The remaining 80% are

humic substances, residues from the decomposition of plants and animals29. Sulfur

constitutes about 0.5% to 2.0% by weight in DOM, mostly occurs as reduced sulfide and

thiol, or as oxidized sulfonate, sulfate). Xia et al. estimated the reduced sulfur content in

Suwannee humic mater is 35-46% of total sulfur.

DOM is ubiquitous in natural waters, and its binding capability affects speciation,

solubility, mobility, and toxicity of trace metals. Reduced sulfur sites, due to its high

affinity, provides most binding sites for mercury30. The interaction between DOM and

Hg has been marked by positive correlations between their concentrations in many

natural waters1. However, since binding of Hg to DOM is dominated by reactive thiol

functional group, a positive correlation may not always exist between Hg and DOM

concentration31. Humic and fulvic acid fractions in DOM can reduce ionic mercury to

elemental Hg32, DOM is able to enhance photochemical reactions of Hg0 from HgII 33.

Abiotic or chemical methylation of mercury is feasible when suitable methyl donors are

present, even if the methylating reagent is a biological product. Some reagents have been

proposed are methyl iodide and dimethylsulfide, fulvic and humic acids in DOM,

organometallic complexes such as methylcobalamin, methyllead or methyltin

compounds34. According to Krishnamurthy (1992), the methyl group can transfer via the

forms of carbocationic Me+, carbanionic Me_ or radical Me, depending on the methylate

agents.

Methylcobalt(III) compounds are potential methylate agents of free HgII, demonstrated

in the below equation

𝑀𝑒𝐶𝑜(𝑑𝑚𝑔)2𝐻2𝑂 + 𝐻𝑔2+ → 𝐶𝑜(𝑑𝑚𝑔)2(𝐻2𝑂)2+ + 𝑀𝑒𝐻𝑔+(5)

The reaction is pH-dependent. In salinity environment such as seawater, the decay of

methylcobaloxime was negligible34.

Another possible reagent is methyltin, which may take account for 90% of aquatic

organotin (Donard et al.,1986). This general methylation reaction was proposed by Celo

et al, (2003)

𝑀𝑒𝑛𝑆𝑛 (𝐼𝑉) + 𝐻𝑔 (𝐼𝐼) → 𝑀𝑒𝑛−1𝑆𝑛 (𝐼𝑉) + 𝑀𝑒𝐻𝑔 (𝐼𝐼) (6)

These reactions are faster at higher pH and require the presence of chloride, therefore, it

should be more important in seawater34.

The most abundant reagents in DOM are humic and fulvic acid. The speciation of Hg

(II) in solutions determines the MeHg formation. Relative rates and yields were

11

estimated to follow the order: Hg(NO3)2 (pH 4) > > Hg(NO3)2 (pH 6) > > HgCl2 (pH 4

or 6). An electrophilic attack by Hg2+(aq) on fulvic acid was proposed for the abiotic

methylation26.

4.6 Minimizing artifactual methylation

After identifying the abiotic methylation process in DOM, we have the second objective,

to minimize the level of artifact MeHg. However, within the allotted time, we have not

come up with a feasible solution. Organic matrixes are ubiquitous, and alteration of the

matrixes will cause changes in the actual MeHg concentration.

A possible solution may include a correction factor, or a different methylation model.

Hintelmann et al (1997) used a linear regression with extrapolation to “zero”

concentration of ambient MeHg, to calculate the “actual” concentration of MeHg8. This

was applied to sediment reference material IAEA 356. The causes of artifact methylation

in sediment was proved to be in the sample preparation steps, including distillation and

leeching. The lack of reference material in water will cause great difficulties if we are to

apply the same methods, but it is still a possibility that we can have some mathematical

solutions to artifact methylation in waters.

5. Conclusions

This study examined the sources of artifact methylation in natural water. Acetate buffer

does not have any significant contribution in our experiment condition. The main source

has found to be storage of inorganic mercury in organic matrixes, which can yield as

much as 0.3%-1.25% methylation percentage. This could cause a significant

overestimation of methylmercury in water, where concentrations of mercury are lower

and bacterial activities are less active, in comparison to sediment. We also concluded

that various water samples including both artificial and natural, have different

methylation percentage and the phenomenon could not be explained solely by DOM-

content.

6. Outlook

Abiotic methylation of inorganic mercury in aqueous system explained the artifact

MeHg formed in organic-rich water samples. However, there are intriguing questions

that we have not yet answered, such as other factors affecting DOM-methylation (pH,

temperature, the content of sulfur, etc.). It is also a challenge to reduce or compensate

for artifactual methylation, as removing the organic matrix entirely will affect the actual

concentration, as well as misrepresenting the native mercury environment. Therefore,

within the scope of this project, we have found the source of abiotic methylation, but a

thorough solution has not been devised due to limited time. We might need a correction

factor or another model to determine the more accurate MeHg concentration, regarding

the different levels of artifacts for each type of natural waters.

Acknowledgment

I would like to thank my supervisors, Erik and Alex for always supporting me in this

project, from guiding me how to use the instrument, to water sampling and experiment

designing. I also want to thank Khoa for all our discussions and your guidance in lab;

your company has been invaluable to me. Other thanks go to my seniors and friends,

Thuy, Phuoc, Liem, Chau, Hien, Van, Tan, Tu. Thanks to Khue Tu, my best friend, and

all the amazing people back home for always cheering me up and making me believe

that I am capable. And most important of all, I would like to express my love and

gratitude to my parents, who have always supported my decision studying in Sweden.

12

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14

Appendix I: Matrix deconvolution method to calculate

concentrations of methylmercury

In mathematics and, in particular, functional analysis, convolution is a mathematical

operation on two functions f and g, producing a third function that is typically viewed

as a modified version of one of the original functions, giving the area overlap between

the two functions as a function of the amount that one of the original functions

is translated. 𝑓(𝑥) ∗ 𝑔(𝑥) → ℎ (𝑥)

The reverse process is called deconvolution and can be expressed as ℎ (𝑥) → 𝑓(𝑥) ∗ 𝑔(𝑥)

The isotope intensity measured (GC-ICP MS) is a convolute of:

Amounts of tracer and ambient Hg (mole)

Isotopic composition of tracer and ambient Hg (ratio)

Let us take the most prevalent calculation in this project as the demonstration of matrix

deconvolution, with 3 isotopes (A) CH3200Hg as an IDA standard (B) 198Hg tracer (and

will be interpreted as artifacts), and (C) Isotope 202 for ambient Hg. We need to

determine the following factors, so as to calculate the concentration of each components:

The signal contribution from the CH3200Hg IDA standard to the total measured

signal at m/z 200

The signal contribution from the 198Hg tracer to the total measured signal at m/z

198

The signal contribution from ambient CH3Hg to the total measured signal at m/z

202

In the convoluted signals, all three isotope components contribute to the measured

signal at each m/z.

Σ 𝑆𝑖𝑔𝑛𝑎𝑙198 = 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴198 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐵

198 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐶198 (𝐴. 1)

Σ 𝑆𝑖𝑔𝑛𝑎𝑙200 = 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴200 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐵

200 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐶200 (𝐴. 2)

Σ 𝑆𝑖𝑔𝑛𝑎𝑙202 = 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴202 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐵

202 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐶202 (𝐴. 3)

To reduce the number of unknown, we must rewrite the equations, with input from the

known isotope distribution pattern for each components. All signal contributions from

component A can be expressed as a function of A’s signal contribution to its major

isotope, i.e. as A’s signal contribution to the major isotope multiplied with A’s

theoretical isotope ratio between the isotope of interest and A’s major isotope.

Table A1: Isotope distribution pattern (%)

Isotope A (198Hg tracer) B (CH3200Hg

standard)

C (Natural)

198 92.78 0.13 0.100

200 1.09 96.41 0.231

202 0.52 0.91 0.298 The intensity measured (Signal) is directly proportional to the amount (concentration) of Hg.

Isotopic distribution is denoted as ID

15

𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴200

𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴198 =

𝐼𝐷𝐴200

𝐼𝐷𝐴198 (𝐴. 4)

→ 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴200 = 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴

198 × 𝐼𝐷𝐴

200

𝐼𝐷𝐴198 (𝐴. 4.1)

𝐼𝐷𝐴200 (=1.09)

𝐼𝐷𝐴198(=91.95)

is denoted as 𝑅𝐴200/198

Then, we can finally rewrite equations A1-A3 to 3 equations and 3 unknowns

Σ 𝑆𝑖𝑔𝑛𝑎𝑙198 = 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴198 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐵

200 × 𝑅𝐵198/200

+ 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐶202 × 𝑅202

199 (𝐴. 5)

Σ 𝑆𝑖𝑔𝑛𝑎𝑙200 = 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴198 × 𝑅𝐴

200/198+ 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐵

200 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐶202 × 𝑅198

200 (𝐴. 6)

Σ 𝑆𝑖𝑔𝑛𝑎𝑙202 = 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴198 × 𝑅𝐴

202/198+ 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐵

200 × 𝑅200202 + 𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐶

202 (𝐴. 7)

In matrix notation, it can be written as AX = B, with

𝐴 =

1 𝑅𝐵198/200

𝑅𝐶198/202

𝑅𝐴200/198

1 𝑅𝐶200/202

𝑅𝐴202/198

𝑅𝐵202/200

1

𝑋 =

𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐴198

𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐵200

𝑆𝑖𝑔𝑛𝑎𝑙𝑓𝑟𝑜𝑚 𝐶202

𝐵 =

Σ 𝑆𝑖𝑔𝑛𝑎𝑙198

Σ 𝑆𝑖𝑔𝑛𝑎𝑙200

Σ 𝑆𝑖𝑔𝑛𝑎𝑙202

We can solve X = B A-1 by Mathlab or function mmult and minverse in Excel

For more components, the deconvolution process can be done with the same principles.

16