Mercury is ubiquitous in the atmosphere, and atmospheric transport is an important source for this element in the Arctic. Measurements of gaseous elemental mercury (GEM) have been carried out at Villum Research Station (Villum) at Station Nord, situated in northern Greenland. The measurements cover the period 1999–2017, with a gap in the data for the period 2003–2008 (for a total of 11 years). The measurements were compared with model results from the Danish Eulerian Hemispheric Model (DEHM) that describes the contribution from direct anthropogenic transport, marine emissions and general background concentration. The percentage of time spent over different surfaces was calculated by back-trajectory analysis, and the reaction kinetics were determined by a comparison with ozone.
The GEM measurements were analysed for trends, both seasonal and annual. The only significant trends found were negative ones for the winter and autumn months. Comparison of the measurements to simulations using the Danish Eulerian Hemispheric Model (DEHM) indicated that direct transport of anthropogenic emissions of mercury accounts for between 14 % and 17 % of the measured mercury. Analysis of the kinetics of the observed atmospheric mercury depletion events (AMDEs) confirms the results of a previous study at Villum of the competing reactions of GEM and ozone with Br, which suggests that the lifetime of GEM is about a month. However, a GEM lifetime of 12 months gave the best agreement between the model and measurements. The chemical lifetime is shorter, and thus, the apparent lifetime appears to be the result of deposition followed by reduction and re-emission; for this reason, the term “relaxation time” is preferred to “lifetime” for GEM. The relaxation time for GEM causes a delay between emission reductions and the effect on actual concentrations.
No significant annual trend was found for the measured concentrations of GEM over the measurement period, despite emission reductions. This is interesting, and together with low direct transport of GEM to Villum as found by the DEHM model, it shows that the dynamics of GEM are very complex. Therefore, in the coming years, intensive measurement networks are needed to describe the global distribution of mercury in the environment as the use of models to predict future levels will still be highly uncertain. The situation is increasingly complex due to global changes that most likely will change the transport patterns of mercury, not only in the atmosphere but also between matrixes.
The effects of long-range atmospheric transport of anthropogenic pollutants into the Arctic are well documented; contaminants are affecting the Arctic by the contamination of food chains and by altering the radiation budget, thus contributing to climate change (UNEP, 2013; AMAP/UNEP 2013; Heidam et al., 2004; Breider et al., 2017). There are still only a few local sources of pollutants in the Arctic, and long-range transport, mainly from mid-latitudes, represents the main source.
Mercury (Hg) is one of the first substances that has been identified as a pollutant in the food web worldwide, causing adverse effects on human health and wildlife. The Minamata Convention, aiming to reduce the exposure of human beings and the environment to mercury, was signed in 2013 (UNEP, 2013), and it entered into force in 2017.
The sources of mercury in the environment can be divided into terrestrial
emissions (including geogenic, biomass burning and re-emissions from soils
and vegetation), anthropogenic and oceanic emissions accounting for 2.1, 2.5
and 3.4 ktonnes of the emissions, respectively (Outridge et al., 2018). This
is in good agreement with other estimates. The global anthropogenic
emissions of mercury were estimated as being 2.5 ktonnes in 2010 (UNEP, 2013; AMAP/UNEP, 2013), and including the large uncertainty of these numbers, they are not significantly different. According to an estimate by (Pirrone et al., 2010) natural sources and re-emission processes (hereafter referred to as background sources), accounted for 5207 Mg yr
The geographical distribution of the emissions has changed in the last few
decades, where Asian countries have gained importance compared to emissions
in Europe, North America and Japan. Today, China accounts for about 40 %
of the global Hg emissions (Muntean et al., 2014; Streets et al., 2019, 2017,
2018). In North America, Europe and on the North Atlantic, there is a decline in the GEM concentration of between
The aim of the present article is to present and discuss the long time series of GEM measurements at Villum Research Station (Villum) at Station Nord in northern Greenland, with a focus on observed interannual and seasonal trends, and the likely explanations for these in terms of sources, transport patterns and dynamics.
Villum at Station Nord in North Greenland is the
second-most northerly, permanently open station in the Arctic, preceded only
by Alert, Canada. The station has all the logistic requirements and
infrastructure that are necessary for being a major international platform
for scientific studies focused on the Arctic cryosphere, nature and
interaction with humans. It is located in the furthermost northeastern corner
of Greenland on the north–south oriented peninsula of Princess Ingeborg
Halvø (81
The position of Villum Research Station at Station Nord in northern Greenland. The blue area represents the Greenland National Park.
Map of Villum Research Station with its buildings (blue) relative to the Station Nord military outpost. Flyger's hut and the Air Observatory are located about 2 km outside main base of Station Nord. Until 2014, all measurements were performed at Flyger's hut; thereafter, they were moved to the Air Observatory.
Since 1999, GEM has been measured by a Tekran 2537 mercury analyser. In the
first few years, funding was only available for 6 months per year of
observations, and thus, the data coverage over the entire year is limited to spring, summer and early autumn, except for the very first year. There are no measurements available for the years 2003–2008 as the research station was closed. Several generations of the instrument have been used (A, B and X
versions), but we estimate that the uncertainty of measuring GEM has remained
unchanged over the years as they are all calibrated towards the same
standard, based on the vapour pressure of Hg
Ozone has been measured since 1996. Though different instruments have been
applied, the measurement uncertainty is unchanged, as the basic principle in
all instruments is the absorption of UV light at 254 nm. The stability of the instruments is ensured by the addition of known concentrations of ozone from an internal ozone generator traceable to a primary standard. The uncertainty at a 95 % confidence level is
The calculation of interannual trends was performed by applying the non-parametric Mann–Kendall test and Sen's slope calculation, using the programme developed by Salmi et al. (2002).
We have applied the Danish Eulerian Hemispheric Model (DEHM) to calculate
the concentrations and direct contributions from different source areas to
the concentration levels in the air at Villum as a function of a prescribed
chemical lifetime of Hg
DEHM is a 3D, offline, large-scale, Eulerian, atmospheric chemistry transport model (CTM) developed to study the long-range transport of air pollution in the Northern Hemisphere, with a focus on the Arctic or Europe. The model domain used in previous studies covers most of the Northern Hemisphere, discretised on a polar stereographic projection, and includes a two-way nesting procedure with several nests with higher resolution over Europe, Northern Europe and Denmark or the Arctic (Frohn et al., 2002; Brandt et al., 2012).
DEHM was originally developed in the early 1990s to study the atmospheric transport of sulfur and sulfate into the Arctic (Christensen, 1997; Heidam et al., 1999, 2004), and it has been used to study the transport of mercury to the Arctic (Christensen et al., 2004; Skov et al., 2004).
The model system has been set up with one model domain with 150
The DEHM model is driven by meteorological data from the Advanced Research Weather Research and Forecasting model version 3.6 (WRF–ARW; Skamarock et al., 2008). This WRF model simulation was driven by global meteorological ERA-Interim data, which are a global atmospheric reanalysis data set from the European Centre for Medium-Range Weather Forecasts (ECMWF), starting from 1979 and being continuously updated in real time. These data have been inserted into the WRF model every 6 h. The WRF model has been run in a climate mode set-up, e.g.continuously updating sea surface temperature and deep soil temperature (both from the ERA-Interim).
The global historical AMAP Hg emissions inventories for 1990–2010 have been used as the anthropogenic emissions (AMAP/UNEP, 2013) for the model run with variable emissions. The 1990 emissions have been used for the model calculations for the period 1990–1992, 1995 emissions for the years 1993–1997, 2000 emissions for 1998–2002, 2005 emissions for 2003–2007 and, finally, the 2010 emissions for 2008–2017. The emissions for 2005 were used for the model run with constant emissions.
Emissions of mercury from biomass burning were based on CO emissions
obtained from the Global Fire Emissions Database version 3 (van der Werf
et al., 2006), where a fixed Hg
The system has been set up with 11 different GEM tracers which represent
eight different anthropogenic source areas (Russia, Eastern Europe, Western
Europe, China, North America, the rest of Asia, Africa and South America) and
biomass burning, ocean sources and the prescribed boundary conditions on 1.5 ng m
There have been 2
In order to investigate the influence of different surfaces on the GEM
concentration, 120 h back trajectories for air masses arriving at 100 m
altitude at Villum were calculated with an hourly resolution using the British Atmospheric Data Centre (BADC) trajectory service. For each of the
trajectories, the time spent over different surfaces was calculated using a
polar stereographic map of the Northern Hemisphere, where each of the
1024
The measurements of GEM and ozone from 1996 to 2017 are shown in Fig. 3. A
seasonal pattern is observed for each year (see Fig. 4). In January and
February, the level of ozone and GEM is rather stable. After the polar
sunrise, the concentration starts to fluctuate strongly, and ozone and GEM
are depleted quickly (within 2 to 10 h). Figure 5 shows the variations
in the yearly average GEM concentration and the average for the winter
season between 1999 and 2018, where only periods with more than 50 % data
coverage have been included. The annual averages show a negative trend;
however, it is not significant at a 90 % confidence level. The autumn
(September, October and November – SON) and the winter months both show negative trends that are significant at a 90 % confidence level. The trends, in a percentage of the average GEM concentrations during these periods, are
Time series of the concentration of GEM and the mixing ratio of ozone at Villum Research Station.
Monthly averages of GEM for the years 1999 to 2002 and 2008 to
2018 at Villum Research Station. The spread in monthly mean value is shown
as
Yearly (orange) and winter season (December, January and February – DJF; blue) average values of measured GEM concentrations at Villum, with trend lines.
The strongest concentration trend is found during the winter, when
photochemically driven chemistry obviously does not take place in the area,
but where long-range transport from mid-latitudes is at its maximum. The
main influence of Arctic atmospheric chemistry on GEM concentrations is
expected to be in the spring and summer period, when the fate of GEM is
believed to depend on the presence of seasonal sea ice and the presence of
air temperatures below
The mercury cycle in the Arctic atmosphere, where gaseous
elemental mercury (Hg
The data until 2002 were used to investigate the reaction kinetics of ozone and GEM with a third reactant. Log–log plots of ozone against GEM gave a
straight line, as seen earlier (Schroeder et al., 1998; Berg et al., 2003;
Steffen et al., 2008; Skov et al., 2004). A reaction rate for Br with Hg
The seasonally averaged concentration has a maximum in the summer (June, July and August – JJA) and a minimum in the spring (March, April and May – MAM). In order to test the hypothesis that the spring minimum is related to the occurrence of the combined mercury and ozone depletion events, an indicator of the duration and frequency of such depletion episodes was created. The number of measured hourly GEM concentrations below 50 % of the average value in a previous event-free period was compared, as a percentage, to the total number of available hourly measurements during the period of interest. For the MAM period, this percentage of AMDE hours was found to be strongly correlated with the average GEM concentrations in the same period (Fig. 7). Thus, there is evidence for a strong impact of AMDE on GEM concentrations in the spring period. The frequency of AMDE in spring and GEM concentration in summer showed a poor negative correlation. If the deposited Hg during AMDE should be released again during snowmelt, a positive correlation would have been expected, but this was not observed. In fact, the analyses indicate that AMDE is a net sink for mercury, which is in agreement with direct flux measurements (Brooks et al., 2006). Interestingly, Angot et al. (2016) found a positive feedback between AMDE in spring and the concentration of GEM in summer at Alert that was attributed to the re-emission of mercury. Contrary to this result, even the annual mean value at Villum had a negative correlation with AMDE hours. Though this correlation is weak, it is an indication that AMDEs affect the GEM concentration level at Villum and represent a net sink. From studies of mercury isotopes at Utqiaġvik on the north coast of Alaska (Douglas et al., 2019) and Toolik research station in central Alaska (Jiskra et al., 2019), it was found that most mercury in meltwater was from the deposition of GEM, and that a large majority of deposited oxidised mercury during AMDE was reduced and reemitted. Further studies are needed to determine if these results are also valid for more northern Arctic locations such as Alert, Villum or Zeppelin.
Frequency of depletion episodes versus average GEM concentration
in March, April and May (MAM). Unit: ng m
It has been determined that outflows from rivers are a main source of Hg in the Arctic Ocean (e.g. Outridge et al., 2008; Fischer et al., 2012). The present study indicates that there is an atmospheric input as well. The significance of this source depends on its chemical form. Previously, atmospheric deposited mercury has been identified to be bioavailable (Moller et al., 2011) and, thus, might still be dominant for the mercury found in the Arctic food web.
Recent studies show that mercury emissions from Europe and North America
have been decreasing since 1990, while emissions in Asia have been
increasing (AMAP/UNEP, 2013; Muntean et al., 2014). Russian emissions, considered as a separate entity, have been decreasing as well. Concentration data from cruises on the North Atlantic show a declining trend since 1990, with a steep decrease in the surface seawater Hg
Model calculations with variable emissions of the source
apportionment of the direct anthropogenic contribution to the annual average
GEM concentrations at Villum. The DEHM model was used for 2 years (1990 and 1991) to spin up the model. Source regions: Russia – Russia; EEU – eastern Europe; WEu – western Europe; China – China; Africa – Africa; SAm – South America. Unit: ng m
Model calculations with variable emissions of the source
apportionment of annual average GEM at Villum. The DEHM model was used for 2 years (1990 and 1991) to spin up the model. In the model, re-emissions from the ocean and contributions from boundary conditions at the Equator are included. Source regions: Russia – Russia; EEU – eastern Europe; WEu – western Europe; China – China; Africa – Africa; SAm – South America; Bound – boundary condition; Ocean – ocean; Fire – wildfire. Unit: ng m
The DEHM model, using variable anthropogenic emissions, as described above,
shows a slightly decreasing concentration trend of
In the calculations with DEHM, it was found that emissions from China had
larger relative importance during the summer than in the winter season;
however, this difference was only significant when applying relatively short
(less than 1 year) atmospheric lifetimes of GEM. The calculations for Villum
were performed for the year 2001. This result agrees with Chen et al. (2015), who found that East Asia is the main source for mercury deposition
in the Arctic. A similar result is also reported by AMAP/UNEP (2013). Durnford
et al. (2010), applying the global/regional atmospheric heavy metals model (GRAHM), investigated the contribution of different source regions to total mercury and GEM concentrations at several Arctic monitoring stations during different seasons of the year. They found that for the yearly concentration averages and their variability at the Arctic stations, including Villum, Asian emissions were the most important, accounting for more than the sum of the contributions from Europe, Russia and North America. This result is in agreement with the present study but in contrast with several studies addressing the origin of shorter lived pollutants, such as black carbon and sulfate, that point to the northerly part of Eurasia as the main source regions (Nguyen et al., 2013; Freud et al., 2017). Particularly in the case of Station Nord (now named Villum Research Station), Nguyen et al. (2013) found evidence of a strong influence of the direct transport of particles from Siberia, including results from previous work (Heidam et al., 2004). Heidam et al. (2004) identified Russia as the main contributor to sulfate concentrations, followed by Eastern and Western Europe, while Asian contributions appeared to be of minor importance. The explanation for this difference between modelling results regarding mercury and more short-lived air pollutants is likely to be the large difference in atmospheric lifetimes (relaxation time for GEM). The above discussion highlights the importance of assessing the chemistry of GEM and determining the fate of the resulting reaction products, especially the photoreduction of Hg
Results obtained by applying the DEHM model to simulate GEM concentrations
at Villum indicate that changes in the direct atmospheric transport from
source areas to Villum cannot explain the observed trend. We have found that
the simulated yearly and seasonal GEM values show very little variability
and no significant trend over the years 2000–2015 when the emission
sources are kept constant at the 2005 level, while the meteorology is
varying and treated as described above. That is opposite to the results of
Dastoor et al. (2015) for a model run with constant emissions. The main
reason for this is probably that processes, such as chemistry and surface
exchanges in Dastoor et al. (2015), are more dependent on the atmosphere and
surface conditions than the simple set-up in the present version of DEHM.
There is better agreement between our results and Dastoor et al. (2015) for
the model set-up with variable emissions. We see a decrease of 0.08
ng m
The correlation of the time that air masses spent over different
surfaces, and the GEM concentration shown for the different seasons (DJF – December, January and February; MAM – March, April and May; JJA – June, July and August; SON – September, October and November.). Values for both
In an earlier paper on particle formation in the Arctic atmosphere,
important results were obtained that correlated the time that air masses spent over different surfaces and measured concentrations (Dall'Osto et al., 2018). We did the same calculations for the GEM data. The correlations between the time that air masses passed over different surfaces and the measured GEM concentrations at Villum are shown in Table 1. Relatively strong negative correlations (
In this paper, we present measurements of GEM concentrations in the air at Villum Research Station from 1999 to 2017, with a break in the data set from July 2002 to 2007. The large fraction of GEM assigned to background contribution and from sea emissions makes it difficult to assess a trend from the otherwise predicted emission reduction in the source areas for direct anthropogenic emissions of mercury. A decreasing trend in the concentration of GEM was found during autumn and winter at a 90 % confidence level, but it was counteracted by a weak increase during summer and a high variability during spring. Therefore, there was not any significant trend in the yearly average concentrations at the 90 % confidence level.
Simulations of the concentrations at Villum, using the DEHM model with a
fixed emission inventory, show no significant trends, and thus, it is concluded that the observed trends are not caused by changes in atmospheric transport patterns. The measurement area is known to be strongly influenced by long-range transport of pollutants in the winter and spring periods, and the only viable explanation of the observed trend in the winter appears to be
decreasing emissions in the source regions. However, according to the DEHM
simulations, the transport of direct anthropogenic emissions only accounted
for between 14 % and 17 % of the GEM concentration and might be
counteracted by the hemispheric background on 1.5 ng m
The seasonal variation confirms the effect of AMDE, leading to generally lower concentrations during spring; in fact, a strong anti-correlation between the average GEM concentrations during springtime and the number of hours with AMDE conditions was observed. The analyses indicated that AMDEs are a net sink for mercury in the atmosphere, and that it affects the yearly average concentration.
Simulations with the DEHM model showed the best agreement with observations applying an atmospheric lifetime for GEM of 12 months; however, it was found that the apparent lifetime is likely to be the result of a shorter chemical lifetime with respect to oxidation followed by deposition, reduction and re-emission. Thus, “atmospheric relaxation time” seems to be a more appropriate term than “lifetime” for GEM.
The lack of a trend in the measured concentrations of GEM, despite emission reductions, is striking, but together with low direct transport of GEM to Villum as found by the DEHM model, it shows that the dynamics of GEM are very complex. Therefore, in the coming years, intensive measurement networks are strongly needed to describe the global distribution of mercury in the environment because the use of models to predict future levels will still be highly uncertain. The situation is increasingly complex due to global change that most likely will change the transport patterns of mercury, not only in the atmosphere but also between matrixes.
The measurements are derived from the European Monitoring and Evaluation Programme, Arctic Monitoring and Assessment Program, World Data Centre for Aerosols database (
All co-authors were involved in the scientific discussions of the paper. HS was the project leader and principal writer. JH was the co-writer and coordinated the statistical analysis. BJ and CC conducted the calibration, tests and set up the instruments. CN made the quality control measurements. MBP led the trend analysis and the analysis of the relation between ozone and GEM, while JBL performed the analysis of the depletion events. DB and MD'O conducted the trajectory clustering analysis and collected the K statistics, with MD'O also contributing to the overall design of article. JHC was responsible for the model calculations by DEHM.
The authors declare that they have no conflict of interest.
This article is part of the special issue “Research results from the 14th International Conference on Mercury as a Global Pollutant (ICMGP 2019), MercOx project, and iGOSP and iCUPE projects of ERA-PLANET in support of the Minamata Convention on Mercury (ACP/AMT inter-journal SI)”. It is not associated with a conference.
The Royal Danish Air Force is acknowledged for providing free transport of the equipment to Station Nord, and the staff at Station Nord are especially acknowledged for their excellent technical support. The Villum Foundation is gratefully acknowledged for financing the new research station, namely the Villum Research Station. Daniel Charles Thomas and Jakob Boyd Pernov are acknowledged for their assistance with proofreading and the language adjustments to the paper. The anonymous referees are acknowledged for their constructive comments.
This research has been supported by the Danish Environmental Protection Agency (DANCEA funds for Environmental Support to the Arctic Region project; grant no. 2019-7975) and by the European ERA-PLANET projects of iGOSP and iCUPE (consortium agreement no. 689443 for both projects).
This paper was edited by Ashu Dastoor and reviewed by two anonymous referees.