Convective forcing of mercury and ozone in the Arctic boundary layer induced by leads in sea ice.

The ongoing regime shift of Arctic sea ice from perennial to seasonal ice is associated with more dynamic patterns of opening and closing sea-ice leads (large transient channels of open water in the ice), which may affect atmospheric and biogeochemical cycles in the Arctic. Mercury and ozone are rapidly removed from the atmospheric boundary layer during depletion events in the Arctic, caused by destruction of ozone along with oxidation of gaseous elemental mercury (Hg(0)) to oxidized mercury (Hg(II)) in the atmosphere and its subsequent deposition to snow and ice. Ozone depletion events can change the oxidative capacity of the air by affecting atmospheric hydroxyl radical chemistry, whereas atmospheric mercury depletion events can increase the deposition of mercury to the Arctic, some of which can enter ecosystems during snowmelt. Here we present near-surface measurements of atmospheric mercury and ozone from two Arctic field campaigns near Barrow, Alaska. We find that coastal depletion events are directly linked to sea-ice dynamics. A consolidated ice cover facilitates the depletion of Hg(0) and ozone, but these immediately recover to near-background concentrations in the upwind presence of open sea-ice leads. We attribute the rapid recoveries of Hg(0) and ozone to lead-initiated shallow convection in the stable Arctic boundary layer, which mixes Hg(0) and ozone from undepleted air masses aloft. This convective forcing provides additional Hg(0) to the surface layer at a time of active depletion chemistry, where it is subject to renewed oxidation. Future work will need to establish the degree to which large-scale changes in sea-ice dynamics across the Arctic alter ozone chemistry and mercury deposition in fragile Arctic ecosystems.

A versatile method for groundwater vulnerability projections in future scenarios.

Water scarcity and associated risks are serious societal problems. A major challenge for the future will be to ensure the short-term and long-term provision of accessible and safe freshwater to meet the needs of the rapidly growing human population and changes in land cover and land use, where conservation and protection play a key role. Through a Bayesian spatial statistical method, a time-dependent approach for groundwater vulnerability assessment is developed to account for both the recent status of groundwater contamination and its evolution, as required by the European Union (Groundwater Directive, 2006/118/EC). This approach combines natural and anthropogenic factors to identify areas with a critical combination of high levels and increasing trends of nitrate concentrations, together with a quantitative evaluation of how different future scenarios would impact the quality of groundwater resources in a given area. In particular, the proposed approach can determine potential impacts on groundwater resources if policies are maintained at the status quo or if new measures are implemented for safeguarding groundwater quality, as natural factors are changing under climatic or anthropogenic stresses.

Snowpack measurements suggest role for multi-year sea ice regions in Arctic atmospheric bromine and chlorine chemistry.

As sources of reactive halogens, snowpacks in sea ice regions control the oxidative capacity of the Arctic atmosphere. However, measurements of snowpack halide concentrations remain sparse, particularly in the high Arctic, limiting our understanding of and ability to parameterize snowpack participation in tropospheric halogen chemistry. To address this gap, we measured concentrations of chloride, bromide, and sodium in snow samples collected during polar spring above remote multi-year sea ice (MYI) and first-year sea ice (FYI) north of Greenland and Alaska, as well as in the central Arctic, and compared these measurements to a larger dataset collected in the Alaskan coastal Arctic by Krnavek et al. (2012). Regardless of sea ice region, these surface snow samples generally featured lower salinities, compared to coastal snow. Surface snow in FYI regions was typically enriched in bromide and chloride compared to seawater, indicating snowpack deposition of bromine and chlorine-containing trace gases and an ability of the snowpack to participate further in bromine and chlorine activation processes. In contrast, surface snow in MYI regions was more often depleted in bromide, indicating it served as a source of bromine-containing trace gases to the atmosphere prior to sampling. Measurements at various snow depths indicate that the deposition of sea salt aerosols and halogen-containing trace gases to the snowpack surface played a larger role in determining surface snow halide concentrations compared to upward brine migration from sea ice. Calculated enrichment factors for bromide and chloride, relative to sodium, in the MYI snow samples suggests that MYI regions, in addition to FYI regions, have the potential to play an active role in Arctic boundary layer bromine and chlorine chemistry. The ability of MYI regions to participate in springtime atmospheric halogen chemistry should be considered in regional modeling of halogen activation and interpretation of satellite-based tropospheric bromine monoxide column measurements.

Evaluating nighttime lights and population distribution as proxies for mappinganthropogenic CO2 emission in Vietnam, Cambodia and Laos.

Tracking spatiotemporal changes in GHG emissions is key to successful implementation of the United Nations Framework Convention on Climate Change (UNFCCC). And while emission inventories often provide a robust tool to track emission trends at the country level, subnational emission estimates are often not reported or reports vary in robustness as the estimates are often dependent on the spatial modeling approach and ancillary data used to disaggregate the emission inventories. Assessing the errors and uncertainties of the subnational emission estimates is fundamentally challenging due to the lack of physical measurements at the subnational level. To begin addressing the current performance of modeled gridded CO2 emissions, this study compares two common proxies used to disaggregate CO2 emission estimates. We use a known gridded CO2 model based on satellite-observed nighttime light (NTL) data (Open Source Data Inventory for Anthropogenic CO2, ODIAC) and a gridded population dataset driven by a set of ancillary geospatial data. We examine the association at multiple spatial scales of these two datasets for three countries in Southeast Asia: Vietnam, Cambodia and Laos and characterize the spatiotemporal similarities and differences for 2000, 2005, and 2010. We specifically highlight areas of potential uncertainty in the ODIAC model, which relies on the single use of NTL data for disaggregation of the non-point emissions estimates. Results show, over time, how a NTL-based emissions disaggregation tends to concentrate CO2 estimates in different ways than population-based estimates at the subnational level. We discuss important considerations in the disconnect between the two modeled datasets and argue that the spatial differences between data products can be useful to identify areas affected by the errors and uncertainties associated with the NTL-based downscaling in a region with uneven urbanization rates.

Wetland monitoring with Global Navigation Satellite System reflectometry.

Information about wetland dynamics remains a major missing gap in characterizing, understanding, and projecting changes in atmospheric methane and terrestrial water storage. A review of current satellite methods to delineate and monitor wetland change shows some recent advances, but much improved sensing technologies are still needed for wetland mapping, not only to provide more accurate global inventories but also to examine changes spanning multiple decades. Global Navigation Satellite Systems Reflectometry (GNSS-R) signatures from aircraft over the Ebro River Delta in Spain and satellite measurements over the Mississippi River and adjacent watersheds demonstrate that inundated wetlands can be identified under different vegetation conditions including a dense rice canopy and a thick forest with tall trees, where optical sensors and monostatic radars provide limited capabilities. Advantages as well as constraints of GNSS-R are presented, and the synergy with various satellite observations are considered to achieve a breakthrough capability for multidecadal wetland dynamics monitoring with frequent global coverage at multiple spatial and temporal scales.