Understanding mercury oxidation and air–snow exchange on the East Antarctic Plateau: a modeling study

Distinct diurnal and seasonal variations of mercury (Hg) have been observed in near-surface air at Concordia Station on the East Antarctic Plateau, but the processes controlling these characteristics are not well understood. Here, we use a box model to interpret the Hg0 (gaseous elemental mercury) measurements in thes year 2013. The model includes atmospheric Hg0 oxidation (by OH, O3, or bromine), surface snow HgII (oxidized mercury) reduction, and air-snow exchange, and is driven by meteorological fields from a regional climate model. The simulations suggest that a photochemically driven mercury diurnal cycle occurs at the air-snow interface in austral summer. The fast oxidation of Hg0 in summer may be provided by a two-step bromine-initiated scheme, which is favored by low temperature and high nitrogen oxides at Concordia. The summertime diurnal variations of Hg0 (peaking during daytime) may be confined within several tens of meters above the snow surface and affected by changing mixed layer depths. Snow re-emission of Hg0 is mainly driven by photoreduction of snow HgII in summer. Intermittent warming events and a hypothesized reduction of HgII occurring in snow in the dark may be important processes controlling the mercury variations in the non-summer period, although their relative importance is uncertain. The Br-initiated oxidation of Hg0 is expected to be slower at Summit Station in Greenland than at Concordia (due to their difference in temperature and levels of nitrogen oxides and ozone), which may contribute to the observed differences in the summertime diurnal variations of Hg0 between these two polar inland stations.National Science Foundation (U.S.) (Grant ACP-1053648

Automated identification of local contamination in remote atmospheric composition time series

Atmospheric observations in remote locations offer a possibility of exploring trace gas and particle concentrations in pristine environments. However, data from remote areas are often contaminated by pollution from local sources. Detecting this contamination is thus a central and frequently encountered issue. Consequently, many different methods exist today to identify local contamination in atmospheric composition measurement time series, but no single method has been widely accepted. In this study, we present a new method to identify primary pollution in remote atmospheric datasets, e.g., from ship campaigns or stations with a low background signal compared to the contaminated signal. The pollution detection algorithm (PDA) identifies and flags periods of polluted data in five steps. The first and most important step identifies polluted periods based on the derivative (time derivative) of a concentration over time. If this derivative exceeds a given threshold, data are flagged as polluted. Further pollution identification steps are a simple concentration threshold filter, a neighboring points filter (optional), a median, and a sparse data filter (optional). The PDA only relies on the target dataset itself and is independent of ancillary datasets such as meteorological variables. All parameters of each step are adjustable so that the PDA can be "tuned" to be more or less stringent (e.g., flag more or fewer data points as contaminated). The PDA was developed and tested with a particle number concentration dataset collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic. Using strict settings, we identified 62 % of the data as influenced by local contamination. Using a second independent particle number concentration dataset also collected during MOSAiC, we evaluated the performance of the PDA against the same dataset cleaned by visual inspection. The two methods agreed in 94 % of the cases. Additionally, the PDA was successfully applied to a trace gas dataset (CO2), also collected during MOSAiC, and to another particle number concentration dataset, collected at the high-altitude background station Jungfraujoch, Switzerland. Thus, the PDA proves to be a useful and flexible tool to identify periods affected by local contamination in atmospheric composition datasets without the need for ancillary measurements. It is best applied to data representing primary pollution. The user-friendly and open-access code enables reproducible application to a wide suite of different datasets. It is available at https://doi.org/10.5281/zenodo.5761101 (Beck et al., 2021).Peer reviewe

Polar oceans and sea ice in a changing climate

Polar oceans and sea ice cover 15% of the Earth’s ocean surface, and the environment is changing rapidly at both poles. Improving knowledge on the interactions between the atmospheric and oceanic realms in the polar regions, a Surface Ocean–Lower Atmosphere Study (SOLAS) project key focus, is essential to understanding the Earth system in the context of climate change. However, our ability to monitor the pace and magnitude of changes in the polar regions and evaluate their impacts for the rest of the globe is limited by both remoteness and sea-ice coverage. Sea ice not only supports biological activity and mediates gas and aerosol exchange but can also hinder some in-situ and remote sensing observations. While satellite remote sensing provides the baseline climate record for sea-ice properties and extent, these techniques cannot provide key variables within and below sea ice. Recent robotics, modeling, and in-situ measurement advances have opened new possibilities for understanding the ocean–sea ice–atmosphere system, but critical knowledge gaps remain. Seasonal and long-term observations are clearly lacking across all variables and phases. Observational and modeling efforts across the sea-ice, ocean, and atmospheric domains must be better linked to achieve a system-level understanding of polar ocean and sea-ice environments. As polar oceans are warming and sea ice is becoming thinner and more ephemeral than before, dramatic changes over a suite of physicochemical and biogeochemical processes are expected, if not already underway.These changes in sea-ice and ocean conditions will affect atmospheric processes by modifying the production of aerosols, aerosol precursors, reactive halogens and oxidants, and the exchange of greenhouse gases. Quantifying which processes will be enhanced or reduced by climate change calls for tailored monitoring programs for high-latitude ocean environments. Open questions in this coupled system will be best resolved by leveraging ongoing international and multidisciplinary programs, such as efforts led by SOLAS, to link research across the ocean–sea ice–atmosphere interface

A central arctic extreme aerosol event triggered by a warm air-mass intrusion

Warm and moist air-mass intrusions into the Arctic are more frequent than the past decades. Here, the authors show that warm air mass intrusions from northern Eurasia inject record amounts of aerosols into the central Arctic Ocean strongly impacting atmospheric chemistry and cloud properties. Frequency and intensity of warm and moist air-mass intrusions into the Arctic have increased over the past decades and have been related to sea ice melt. During our year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia. The two-day intrusion, caused drastic changes in the aerosol size distribution, chemical composition and particle hygroscopicity. Here we show how the intrusion transformed the Arctic from a remote low-particle environment to an area comparable to a central-European urban setting. Additionally, the intrusion resulted in an explosive increase in cloud condensation nuclei, which can have direct effects on Arctic clouds' radiation, their precipitation patterns, and their lifetime. Thus, unless prompt actions to significantly reduce emissions in the source regions are taken, such intrusion events are expected to continue to affect the Arctic climate.Peer reviewe

Year-round trace gas measurements in the central Arctic during the MOSAiC expedition

Despite the key role of the Arctic in the global Earth system, year-round in-situ atmospheric composition observations within the Arctic are sparse and mostly rely on measurements at ground-based coastal stations. Measurements of a suite of in-situ trace gases were performed in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. These observations give a comprehensive picture of year-round near-surface atmospheric abundances of key greenhouse and trace gases, i.e., carbon dioxide, methane, nitrous oxide, ozone, carbon monoxide, dimethylsulfide, sulfur dioxide, elemental mercury, and selected volatile organic compounds (VOCs). Redundancy in certain measurements supported continuity and permitted cross-evaluation and validation of the data. This paper gives an overview of the trace gas measurements conducted during MOSAiC and highlights the high quality of the monitoring activities. In addition, in the case of redundant measurements, merged datasets are provided and recommended for further use by the scientific community.Peer reviewe

A full year of aerosol size distribution data from the central Arctic under an extreme positive Arctic Oscillation : insights from the Multidisciplinarydrifting Observatory for the Study of Arctic Climate (MOSAiC) expedition

The Arctic environment is rapidly changing due to accelerated warming in the region. The warming trend is driving a decline in sea ice extent, which thereby enhances feedback loops in the surface energy budget in the Arctic. Arctic aerosols play an important role in the radiative balance and hence the climate response in the region, yet direct observations of aerosols over the Arctic Ocean are limited. In this study, we investigate the annual cycle in the aerosol particle number size distribution (PNSD), particle number concentration (PNC), and black carbon (BC) mass concentration in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This is the first continuous, year-long data set of aerosol PNSD ever collected over the sea ice in the central Arctic Ocean. We use a k-means cluster analysis, FLEXPART simulations, and inverse modeling to evaluate seasonal patterns and the influence of different source regions on the Arctic aerosol population. Furthermore, we compare the aerosol observations to land-based sites across the Arctic, using both long-term measurements and observations during the year of the MOSAiC expedition (2019-2020), to investigate interannual variability and to give context to the aerosol characteristics from within the central Arctic. Our analysis identifies that, overall, the central Arctic exhibits typical seasonal patterns of aerosols, including anthropogenic influence from Arctic haze in winter and secondary aerosol processes in summer. The seasonal pattern corresponds to the global radiation, surface air temperature, and timing of sea ice melting/freezing, which drive changes in transport patterns and secondary aerosol processes. In winter, the Norilsk region in Russia/Siberia was the dominant source of Arctic haze signals in the PNSD and BC observations, which contributed to higher accumulation-mode PNC and BC mass concentrations in the central Arctic than at land-based observatories. We also show that the wintertime Arctic Oscillation (AO) phenomenon, which was reported to achieve a record-breaking positive phase during January-March 2020, explains the unusual timing and magnitude of Arctic haze across the Arctic region compared to longer-term observations. In summer, the aerosol PNCs of the nucleation and Aitken modes are enhanced; however, concentrations were notably lower in the central Arctic over the ice pack than at land-based sites further south. The analysis presented herein provides a current snapshot of Arctic aerosol processes in an environment that is characterized by rapid changes, which will be crucial for improving climate model predictions, understanding linkages between different environmental processes, and investigating the impacts of climate change in future Arctic aerosol studies.Peer reviewe

Substantial contribution of iodine to Arctic ozone destruction

Unlike bromine, the effect of iodine chemistry on the Arctic surface ozone budget is poorly constrained. We present ship-based measurements of halogen oxides in the high Arctic boundary layer from the sunlit period of March to October 2020 and show that iodine enhances springtime tropospheric ozone depletion. We find that chemical reactions between iodine and ozone are the second highest contributor to ozone loss over the study period, after ozone photolysis-initiated loss and ahead of bromine.Iodine chemistry plays a more important role than bromine chemistry in tropospheric ozone losses in the Arctic, according to ship-based observations of halogen oxides from March to October 2020.Peer reviewe

Atmospheric mercury in the Southern Hemisphere – Part 1: Trend and inter-annual variations in atmospheric mercury at Cape Point, South Africa, in 2007–2017, and on Amsterdam Island in 2012–2017

International audienceThe Minamata Convention on Mercury (Hg) entered into force in 2017, committing its 116 parties (as of January 2019) to curb anthropogenic emissions. Monitoring of atmospheric concentrations and trends is an important part of the effectiveness evaluation of the convention. A few years ago (in 2017) we reported an increasing trend in atmospheric Hg concentrations at the Cape Point Global Atmosphere Watch (GAW) station in South Africa (34.3535∘ S, 18.4897∘ E) for the 2007–2015 period. With 2 more years of measurements at Cape Point and the 2012–2017 data from Amsterdam Island (37.7983∘ S, 77.5378∘ E) in the remote southern Indian Ocean, a more complex picture emerges: at Cape Point the upward trend for the 2007–2017 period is still significant, but no trend or a slightly downward trend was detected for the period 2012–2017 at both Cape Point and Amsterdam Island. The upward trend at Cape Point is driven mainly by the Hg concentration minimum in 2009 and maxima in 2014 and 2012. Using ancillary data on 222Rn, CO, O3, CO2, and CH4 from Cape Point and Amsterdam Island, the possible reasons for the trend and its change are investigated. In a companion paper this analysis is extended for the Cape Point station by calculations of source and sink regions using backward-trajectory analysis

Wind speed measurements with a 2-dimensional ultrasonic anemometer from the FS Polarstern bow tower, deployed during MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) expedition, Arctic Circle, 2019-2020

True and relative wind speed and direction measured from the bow of the research icebreaker FS Polarstern during the 2019-2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) field program. These are minute-averaged values of 1 Hertz (Hz) raw measurements with an RM Young model 86004 heated, 2 Dimensional (2D) ultrasonic anemometer. The measurement location was ~18 meters (m) height on a triangular meteorological tower on the ship's bow, on a horizontal arm extending ~ 1.5m in front of the tower. Sensor heating prevented ice formation in almost all conditions, but there were a few periods of ice build-up in severe freezing rain or fog conditions. The north (N) orientation of the anemometer was in the direction of the ship's bow. True wind speed and direction are computed from relative winds and the ship heading. Due to obstructions from the ship's superstructure, measurements for relative wind directions beyond +/- 130 degrees from the bow are not accurate and subject to high variability. Measurements over the remaining wind sector (+/- 120 deg from the bow) are slightly distorted by the divergence of streamlines over the ship. As a convenience to users, ship navigation parameters (latitude, longitude, speed-over-ground, course-over-ground, and heading) are provided. The archives of ship navigation and meteorological data from PANGEA are the original sources for all navigation parameters (https://doi.org/10.1594/PANGAEA.935221, https://doi.org/10.1594/PANGAEA.935222, https://doi.org/10.1594/PANGAEA.935223, https://doi.org/10.1594/PANGAEA.935224, https://doi.org/10.1594/PANGAEA.935225)

Atmospheric biogenic volatile organic compounds in the Alaskan Arctic tundra: constraints from measurements at Toolik Field Station

The Arctic is a climatically sensitive region that has experienced warming at almost 3 times the global average rate in recent decades, leading to an increase in Arctic greenness and a greater abundance of plants that emit biogenic volatile organic compounds (BVOCs). These changes in atmospheric emissions are expected to significantly modify the overall oxidative chemistry of the region and lead to changes in VOC composition and abundance, with implications for atmospheric processes. Nonetheless, observations needed to constrain our current understanding of these issues in this critical environment are sparse. This work presents novel atmospheric in situ proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) measurements of VOCs at Toolik Field Station (TFS; 68 degrees 38' N, 149 degrees 36' W), in the Alaskan Arctic tundra during May-June 2019. We employ a custom nested grid version of the GEOS-Chem chemical transport model (CTM), driven with MEGANv2.1 (Model of Emissions of Gases and Aerosols from Nature version 2.1) biogenic emissions for Alaska at 0.25 degrees x 0.3125 degrees resolution, to interpret the observations in terms of their constraints on BVOC emissions, total reactive organic carbon (ROC) composition, and calculated OH reactivity (OHr) in this environment. We find total ambient mole fraction of 78 identified VOCs to be 6.3 +/- 0.4 ppbv (10.8 +/- 0.5 ppbC), with overwhelming (> 80 %) contributions are from short-chain oxygenated VOCs (OVOCs) including methanol, acetone and formaldehyde. Isoprene was the most abundant terpene identified. GEOS-Chem captures the observed isoprene (and its oxidation products), acetone and acetaldehyde abundances within the combined model and observation uncertainties (+/- 25 %), but underestimates other OVOCs including methanol, formaldehyde, formic acid and acetic acid by a factor of 3 to 12. The negative model bias for methanol is attributed to underestimated biogenic methanol emissions for the Alaskan tundra in MEGANv2.1. Observed formaldehyde mole fractions increase exponentially with air temperature, likely reflecting its biogenic precursors and pointing to a systematic model underprediction of its secondary production. The median campaign-calculated OHr from VOCs measured at TFS was 0.7 s(-1), roughly 5 % of the values typically reported in lower-latitude forested ecosystems. Ten species account for over 80 % of the calculated VOC OHr, with formaldehyde, isoprene and acetaldehyde together accounting for nearly half of the total. Simulated OHr based on median-modeled VOCs included in GEOS-Chem averages 0.5 s(-1) and is dominated by isoprene (30 %) and monoterpenes (17 %). The data presented here serve as a critical evaluation of our knowledge of BVOCs and ROC budgets in high-latitude environments and represent a foundation for investigating and interpreting future warming-driven changes in VOC emissions in the Alaskan Arctic tundra