Influence of wind speed and wind direction above the sea surface on the diffusive methane flux and the atmospheric methane concentration at the North Sea

The estimations of the diffusive methane flux from the water phase into the atmosphere in coastal waters is relevant for a better estimate of the atmospheric greenhouse-gas budget. Unfortunately, so far, the numerical determination of the fluxes has a high level of uncertainty in coastal waters. To improve the estimation of coastal methane fluxes, not only a high temporal and spatial sampling resolution of the dissolved methane in the water are required. Besides, also the atmospheric methane concentration and the wind speed and wind direction above the surface is important. In most cases, these atmospheric data are obtained from near-by atmospheric and meteorologic monitoring stations. In this study, we measured wind speed, direction and atmospheric methane local directly on board of three research vessel cruising in the southern North Sea within the MOSES project and compared the effects of local versus remote measurements of these data on the flux data. In addition, using the wind direction and speed, we try to assess the origin of the atmospheric methane measured in the study area. Using these “improved” data sets, we discuss if local measurements of auxiliary data provide better insights in the determining factors of the methane flux, and thus also improve the regional aquatic methane budget

High methane production in drained lake basin wetlands in northern Alaska

Wetlands in drained lake basins are important elements of the Arctic carbon budget. They may store large amounts of carbon while also producing substantial amounts of greenhouse gasses. After lake drainage the former lake bottom is colonized by pioneer graminoids, succeeded by mosssedge-dwarf shrub vegetation, producing a typical peat sequence. However, post-drainage organic matter dynamics are not well studied. We hypothesize that vegetation composition reflects both succession and surface wetness, which in turn determine soil organic matter content and methane production. We propose that vegetation types detected by remote sensing-based landcover classification may be used to extrapolate methane production and organic matter composition across drained lake basin landscapes. We investigated (i) plots along a temporal drainage gradient, surveying vegetation, surface sediment, and pond water. We then used (ii) landcover classification of main eco-hydrological classes to (iii) upscale from plot to basin scale. We found that vegetation and organic matter changed markedly between recently drained basins and older age classes. Overall, vegetation composition differed more between eco-hydrological classes than between age classes. Surface sediments had very high water contents (>80 %), suggesting largely anaerobic conditions favouring methane production. Methane concentrations were indeed relatively constant throughout, and particularly high in sediments beneath few centimetres of water (“wet patches”, up to 200 μmol/L) and in pond water (up to 22 μmol/L). Landcover classification yielded seven classes including five classes we also identified using statistical clustering of vegetation data plus a water class and a bare ground class. We found that 67 % of basin areas were occupied by wet patches with especially high methane production. Our study shows that remote sensing-based landcover classifications are useful for quantifying wet-vs-moist patches and high-vs-moderate methane production in Arctic drained lake basins. The study highlights the potential for future upscaling of methane emissions from these abundant wetland environments

Nutrient and carbon dynamics along the river-estuary-ocean continuum on Central European scale

Nutrient and carbon dynamics within the river-estuary-coastal water systems are key processes to understand the matter fluxes from the terrestrial environment to the ocean. In a large-scale study we analysed those dynamics with the focus of the prevailing low water conditions by following a sampling approach based on the travel time of water. We started with a nearly Lagrangian sampling along the River Elbe (German part; 580 km within 8 days travel time). After a subsequent investigation of the estuary, the plume of the river was followed by raster sampling the German Bight (North Sea) using three ships simultaneously. In the river, intensive growth of phytoplankton was determined connected with high oxygen saturation and pH values as well as under-saturation of CO2, whereas concentrations of dissolved nutrients declined. In the estuary, the Elbe shifted from an autotrophic to a heterotrophic system: Phytoplankton died off upstream of the salinity gradient causing minima in oxygen saturation and pH, supersaturation of CO2, and a release of nutrients. In the coastal region, phytoplankton and nutrient concentrations were low, oxygen close to saturation, and pH in a typical marine range. We detected a positive relationship between pH values and oxygen saturation and a negative one between pCO2 and oxygen saturation. Corresponding to the significant particulate nutrient flux via phytoplankton, flux rates of dissolved nutrients from the river into the estuary were low and determined by depleted concentrations. In contrast, fluxes from the estuary to the coastal waters were higher and the pattern was determined by tidal currents. Overall, the presented observation approach is appropriate to better understand land-ocean fluxes, particularly if it is performed under different hydrological conditions including extremes and seems to be suitable to investigate the impact of such events in freshwater on coastal systems in future. The study was conducted within the frame of the Helmholtz MOSES initiative (Modular Observation Solutions for Earth Systems) targeting processes and impacts of hydrological extremes