A dynamical simulation of the fate of atmospheric mercury deposited onto snowpacks

1. A dynamical simulation of the fate of atmospheric mercury deposited onto snowpacks Dorothy Durnford1*, Ashu Dastoor2,Andrei Ryjkov1, Daniel Figueras-Nieto21Independent researcher 2Air Quality Research, Environment Canada AICI Workshop, New York June 6, 2011

2. Motivation It is unknown what fraction of the mercury deposited onto snowpacks is revolatilized. The mercury that is not revolatilized may enter bodies of water with the snowpack meltwater runoff and be converted to toxic methylmercury. In the Arctic, the methylmercury bioaccumulated in fish and large marine mammals poses a serious health risk to those consuming a traditional diet. A dynamic snowpack/meltwater model for mercuryis needed. Since a dynamic model would determine the fate of mercury deposited onto snowpacks solely by means of environmental parameters, such a modelwould help establish the importance of atmospheric deposition as a source of marine mercury. Such a model is also required for studies investigating how a changing climate and changing mercury emissions may affect the transport, deposition and revolatilization of atmospheric mercury in the future.

3. Global atmospheric model for mercury We use Environment Canada’s Global/Regional Atmospheric Heavy Metals model GRAHM. GRAHM is based on Environment Canada’s operational numerical weather prediction model GEM-GDPS. Mercury-related processes, including emissions, transport, chemical reactions, and deposition through dry and wet processes are represented in GRAHM. High-latitude springtime Atmospheric Mercury Depletion Events (AMDEs) are simulated. Base run: uses a global domain, a 1°x1° horizontal resolution, 28/58 levels, and prescribed cryospheric emissions that were calculated from deposition output by previous model runs: prior knowledge of mercury deposition is required. Snowpack/meltwater run: uses a global domain, a 4°x4° horizontal resolution (preliminary results), 28/58 levels, and cryospheric emissions that are a function of mercury deposition during the current model run and the state of the local environment: no prior knowledge of mercury deposition is required.

4. A dynamic snowpack/meltwater model for mercury Lowest atmospheric layer GEM emission: molecular and turbulent diffusions GEM deposition: dry and wet processes Ox Hg deposition: dry and wet processes Top snowpack layer Depth: max 30 cm Total oxidized mercury (OxHg) Gaseous Elemental Mercury (GEM) Net photochemical reduction Snowmelt Molecular diffusion Molecular diffusion Bottom snowpack layer Depth: max 120 cm GEM OxHg Snowmelt Processes active in meltwater: Net photochemical reduction Deposition from the atmosphere in the absence of a snowpack Emission to the atmosphere Snowpack meltwater runoff Depth: variable OxHg

5. Verification of snow-related mercury variables: 1 Verification of snow-related mercury variables a) Concentration of total mercury: top snowpack layer (ng L-1) b) Concentration of total mercury: bottom snowpack layer (ng L-1) d) Fraction of total snowpack mercury contributed by GEM (%) c) Concentration of total mercury: snowpack meltwater runoff (ng L-1) e) Fraction of mercury lost from the top snowpack layer during a 24-h period (%).

6. Verification of snow-related mercury variables: 2 Simulated values: Concentrations of mercury in snowpacks (a, b) are the 5-year (2005-2009) average of monthly average values from the snow season. Concentrations of mercury in snowpack meltwater runoff (c) are the 5-year average of each year’s greatest monthly average concentration. The 24-hour losses of mercury from the top snowpack layer (d) are the 5-year average of monthly average values from the snow season. Periods receiving fresh snow or recording a net gain in mercury are neglected. Observations: Plotted observations represent an average value. They were calculated from data observed during numerous field studies that were reported in the literature. The studies usually spanned a few weeks during spring. Concentrations of mercury in snowpack meltwater runoff are from the ionic pulse, which lasts for a few days. Conclusion: Since we are comparing simulated values from the entire snowpack season to primarily springtime observations, we do not expect a perfect match. Since we expect the heavy averaging to have lowered the simulated values, we consider the simulated concentrations of mercury in snowpacks (a, b) to be reasonable. Since the simulated concentration of mercury in snowpack meltwater runoff (c) is based on monthly averages, which is a far longer time period than the observations’ ionic pulse, the lower simulated concentrations are expected. Low simulated fractions of total snowpack mercury contributed by GEM (d) agree perfectly with observed fractions of typically < 1%. The greater simulated 24-h losses of mercury from surface snow (e) combined with the reasonable simulated concentrations of mercury in snowpacks and runoff may indicate that simulated deposition is too strong.

7. Verification of model performance at stations: 1 Arctic station: Alert a) atmospheric surface-level GEM b) Monthly distribution of the atmospheric GEM concentrations i) Observations ii) Base run iii) Snowpack model iv) Monthly means c) Diurnal cycle of emission of GEM from snowpacks as calculated by the snowpack/meltwater model for mercury

8. Verification of model performance at stations: 2 Midlatitude station: St. Anicet d) atmospheric surface-level GEM e) Monthly distribution of the atmospheric GEM concentrations i) Observations ii) Base run iii) Snowpack model iv) Monthly means f) Diurnal cycle of emission of GEM from snowpacks as calculated by the snowpack/meltwater model for mercury

9. Verification of model performance at stations: 3 I. Atmospheric surface-level GEM concentrations At Alert, the snowpack/meltwater model is able to reproduce the post-AMDE recovery of GEM concentrations during April and May as well as the surge in GEM concentrations at the onset of snowmelt in early June (a, b). The low bias at Alert in July and August (a, b), which negatively impacts the correlation between monthly mean GEM concentrations as observed and simulated (b-iv) indicates that oceanic emissions are important. At St. Anicet, the snowpack/mercury model improves the seasonal cycle of surface-level atmospheric GEM concentrations (d, e), increasing the correlation with the observations (d-iv). The lesser variability produced by the snowpack/meltwater model at both Alert and St. Anicet is a result of its coarse 4-degree resolution. II. The diurnal cycle of cryospheric mercury emissions calculated by the dynamic snowpack/meltwater model for mercury At both Alert and St. Anicet, the diurnal cycle of cryospheric mercury emission (c, f) exhibits a maximum centred slightly after local noon, agreeing with observations. The diurnal signal at Alert is less pronounced than at St. Anicet since the sunlit portion of the days are longer at high latitudes after polar sunrise than at midlatitudes. Emission is greater at Alert as a result of the revolatilization after polar sunrise of mercury deposited on the snow during polar night and during springtime AMDEs.

10. Deposition and emission in the Arctic: 1 Net deposition/emission (μg/m2) Total deposition (μg/m2) Total emission (μg/m2) Dec/Jan/Feb Mar/Apr/May Jun/Jul/Aug Sep/Oct/Nov

11. Deposition and emission in the Arctic: 2 Mercury deposition and Emission polewards of 66.5 °N Little mercury deposition or emission occurs during winter and Fall polewards of 66.5 °N. During spring when AMDEs are active, mercury deposition is so strong in the Arctic that the net deposition of mercury is important despite the significant revolatilization of mercury deposited onto snowpacks. In summer, the deposition of mercury in the Arctic and its revolatilization from snowpacks and snowpack meltwater runoff are still important. Interestingly, we see net deposition from 66.5 to ~80 °N, but net emission polewards of ~80 °N and also over Greenland. The net emission in the central Arctic and over Greenland may reflect the later arrival of sufficient amounts of solar radiation to drive the net reduction of cryospheric oxidized mercury, caused by the high latitudes of the former area and the high altitudes of the latter area. The deposition and emission fields presented are seasonal averages that have been further averaged over 5 years (2005-2009).

12. Conclusion Our dynamic snowpack/meltwater model for mercury yields reasonable results with respect to concentrations of mercury in both snowpacks and the atmosphere. Polewards of 66.5 °N, our results suggest that ~50% of mercury deposited onto snowpacks and snowpack meltwater runoff is revolatilized annually. Net deposition is suggested for the highly active spring season, while both net deposition and net emission are indicated for summer. A big plus: our dynamic snowpack/meltwater model for mercury is fairly inexpensive computationally!

13. Acknowledgements • Gov. of Canada program for the International Polar Year (IPY): INterContinental Atmospheric Transport of anthropogenic Pollutants to the Arctic (INCATPA) • Gov. of Canada’s Clean Air Regulatory Agenda (CARA) • Northern Contaminants Program (NCP) • Sandy Steffen, Hayley Hung: Environment Canada • Torunn Berg, Anne Steen: Norwegian University of Science and Technology