Bromine, iodine and sodium along the EAIIST traverse: Bulk and surface snow latitudinal variability

During the East Antarctic International Ice Sheet Traverse (Eaiist, december 2019), in an unexplored part of the East Antarctic Plateau, snow samples were collected to expand our knowledge of the latitudinal variability of iodine, bromine and sodium as well as their relation in connection with emission processes and photochemical activation in this unexplored area. A total of 32 surface (0-5 cm) and 32 bulk (average of 1 m depth) samples were taken and analysed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Our results show that there is no relevant latitudinal trend for bromine and sodium. For bromine they also show that it has no significant post-depositional mechanisms while its inland surface snow concentration is influenced by spring coastal bromine explosions. Iodine concentrations are several orders of magnitude lower than bromine and sodium and they show a decreasing trend in the surface samples concentration moving southward. This suggests that other processes affect its accumulation in surface snow, probably related to the radial reduction in the ozone layer moving towards central Antarctica. Even though all iodine, bromine and sodium present similar long-range transport from the dominant coastal Antarctic sources, the annual seasonal cycle of the ozone hole over Antarctica increases the amount of UV radiation (in the 280-320 nm range) reaching the surface, thereby affecting the surface snow photoactivation of iodine. A comparison between the bulk and surface samples supports the conclusion that iodine undergoes spring and summer snow recycling that increases its atmospheric lifetime, while it tends to accumulate during the winter months when photochemistry ceases.

Sampling of suspended particulate matter using particle traps in the Rhône River: Relevance and representativeness for the monitoring of contaminants

Monitoring hydrophobic contaminants in surface freshwaters requires measuring contaminant concentrations in the particulate fraction (sediment or suspended particulate matter, SPM) of the water column. Particle traps (PTs) have been recently developed to sample SPM as cost-efficient, easy to operate and time-integrative tools. But the representativeness of SPM collected with PTs is not fully understood, notably in terms of grain size distribution and particulate organic carbon (POC) content, which could both skew particulate contaminant concentrations. The aim of this study was to evaluate the representativeness of SPM characteristics (i.e. grain size distribution and POC content) and associated contaminants (i.e. polychlorinated biphenyls, PCBs; mercury, Hg) in samples collected in a large river using PTs for differing hydrological conditions. Samples collected using PTs (n = 74) were compared with samples collected during the same time period by continuous flow centrifugation (CFC). The grain size distribution of PT samples shifted with increasing water discharge: the proportion of very fine silts (2-6 μm) decreased while that of coarse silts (27-74 μm) increased. Regardless of water discharge, POC contents were different likely due to integration by PT of high POC-content phytoplankton blooms or low POC-content flood events. Differences in PCBs and Hg concentrations were usually within the range of analytical uncertainties and could not be related to grain size or POC content shifts. Occasional Hg-enriched inputs may have led to higher Hg concentrations in a few PT samples (n = 4) which highlights the time-integrative capacity of the PTs. The differences of annual Hg and PCB fluxes calculated either from PT samples or CFC samples were generally below 20%. Despite some inherent limitations (e.g. grain size distribution bias), our findings suggest that PT sampling is a valuable technique to assess reliable spatial and temporal trends of particulate contaminants such as PCBs and Hg within a river monitoring network.

The superstatistical nature and interoccurrence time of atmospheric mercury concentration fluctuations

The probability density function (PDF) of the time intervals between subsequent extreme events in atmospheric Hg⁰ concentration data series from different latitudes has been investigated. The Hg⁰ dynamic possesses a long-term memory autocorrelation function. Above a fixed threshold Q in the data, the PDFs of the interoccurrence time of the Hg⁰ data are well described by a Tsallis q-Exponential function. This PDF behavior has been explained in the framework of superstatistics, where the competition between multiple mesoscopic processes affects the macroscopic dynamics. An extensive parameter μ, encompassing all possible fluctuations related to mesoscopic phenomena, has been identified. It follows a χ ²-distribution, indicative of the superstatistical nature of the overall process. Shuffling the data series destroys the long-term memory, the distributions become independent of Q, and the PDFs collapse on to the same exponential distribution. The possible central role of atmospheric turbulence on extreme events in the Hg⁰ data is highlighted.