Methane distribution at high spatial resolution in North Sea estuaries

Rivers are suspected to be a main suppliers of greenhouse gases (methane and carbon dioxide) to coastal seas, while the role of the interjacent tidal flats is still ambiguous. In this study we investigated the role of the Elbe and Weser estuaries as source of methane to the North Sea. We used high spatially resolved methane measurements from an underway degassing system and subsequent analysis with cavity ring down spectroscopy. Thus, a high-resolution representation of the methane distribution in surface waters as well as of hydrographic parameters was obtained for several cruises with two ships in 2019. For most areas, riverine methane was simply diluted by seawater, overlain by a strong tidal signal. However, on several occasions unexpectedly high methane concentrations were observed. Further detailed analysis will elucidate the role of riverine versus tidal impact on coastal North Sea methane fluxes

Spatial Variability in and Hotspots of Methane Concentration in a Large Temperate River

Rivers are significant sources of greenhouse gases (GHGs; e.g., CH4 and CO2); however, our understanding of the large-scale longitudinal patterns of GHG emissions from rivers remains incomplete, representing a major challenge in upscaling. Local hotspots and moderate heterogeneities may be overlooked by conventional sampling schemes. In August 2020 and for the first time, we performed continuous (once per minute) CH4 measurements of surface water during a 584-km-long river cruise along the German Elbe to explore heterogeneities in CH4 concentration at different spatial scales and identify CH4 hotspots along the river. The median concentration of dissolved CH4 in the Elbe was 112 nmol L−1, ranging from 40 to 1,456 nmol L−1 The highest CH4 concentrations were recorded at known potential hotspots, such as weirs and harbors. These hotspots were also notable in terms of atmospheric CH4 concentrations, indicating that measurements in the atmosphere above the water are useful for hotspot detection. The median atmospheric CH4 concentration was 2,033 ppb, ranging from 1,821 to 2,796 ppb. We observed only moderate changes and fluctuations in values along the river. Tributaries did not obviously affect CH4 concentrations in the main river. The median CH4 emission was 251 μmol m−2 d−1, resulting in a total of 28,640 mol d−1 from the entire German Elbe. Similar numbers were obtained using a conventional sampling approach, indicating that continuous measurements are not essential for a large-scale budget. However, we observed considerable lateral heterogeneity, with significantly higher concentrations near the shore only in reaches with groins. Sedimentation and organic matter mineralization in groin fields evidently increase CH4 concentrations in the river, leading to considerable lateral heterogeneity. Thus, river morphology and structures determine the variability of dissolved CH4 in large rivers, resulting in smooth concentrations at the beginning of the Elbe versus a strong variability in its lower parts. In conclusion, groin construction is an additional anthropogenic modification following dam building that can significantly increase GHG emissions from rivers

Methane dynamics in three different Siberian water bodies under winter and summer conditions

Arctic regions and their water bodies are affected by a rapidly warming climate. Arctic lakes and small ponds are known to act as an important source of atmospheric methane. However, not much is known about other types of water bodies in permafrost regions, which include major rivers and coastal bays as a transition type between freshwater and marine environments. We monitored dissolved methane concentrations in three different water bodies (Lena River, Tiksi Bay, and Lake Golzovoye, Siberia, Russia) over a period of 2 years. Sampling was carried out under ice cover (April) and in open water (July-August). The methane oxidation (MOX) rate and the fractional turnover rate (k') in water and melted ice samples from the late winter of 2017 was determined with the radiotracer method. In the Lena River winter methane concentrations were a quarter of the summer concentrations (8 nmol L-1 vs. 31 nmol L-1), and mean winter MOX rate was low (0.023 nmol L-1 d(-1)). In contrast, Tiksi Bay winter methane concentrations were 10 times higher than in summer (103 nmol L-1 vs. 13 nmol L-1). Winter MOX rates showed a median of 0.305 nmol L-1 d(-1). In Lake Golzovoye, median methane concentrations in winter were 40 times higher than in summer (1957 nmol L-1 vs. 49 nmol L-1). However, MOX was much higher in the lake (2.95 nmol L-1 d(-1)) than in either the river or bay. The temperature had a strong influence on the MOX (Q(10) = 2.72 +/- 0.69). In summer water temperatures ranged from 7-14 degrees C and in winter from -0.7 to 1.3 degrees C. In the ice cores a median methane concentration of 9 nM was observed, with no gradient between the ice surface and the bottom layer at the ice-water interface. MOX in the (melted) ice cores was mostly below the detection limit. Comparing methane concentrations in the ice with the underlaying water column revealed methane concentration in the water column 100-1000 times higher. The winter situation seemed to favor a methane accumulation under ice, especially in the lake with a stagnant water body. While on the other hand, in the Lena River with its flowing water, no methane accumulation under ice was observed. In a changing, warming Arctic, a shorter ice cover period is predicted. With respect to our study this would imply a shortened time for methane to accumulate below the ice and a shorter time for the less efficient winter MOX. Especially for lakes, an extended time of ice-free conditions could reduce the methane flux from the Arctic water bodies

Characteristics of dissolved and atmospheric methane concentrations along a freshwater-seawater transect from the River Elbe into the North Sea

Surface waters are known to be significant sources of greenhouse gases (CH4 and CO2), but our understanding of large scale patterns is still incomplete. The greenhouse gases in rivers originate both from in-stream processes and interactions with the catchment. For coastal seas, rivers are suspected to be one of the main source of greenhouse gases, while the role of the interjacent tidal flats is still ambiguous. Especially the reaction of the entire system on terrestrial hydrological extremes such as low flow situations are still under consideration. The functional understanding of such events and their impacts on the water chemistry along its transition pathway in the terrestrial and limnic compartment as well as in the coastal marine environment is crucially needed for the evaluation of its relevance in the Earth system. As part of a MOSES campaign (Modular Observation Solutions for Earth Systems) spanning disciplines as well as earth system compartments we investigated the aquatic as well as the atmospheric compartemt in and above the Elbe River from inland waters through the tidal section of the river and the estuary to the North Sea with the goal to explore spatial heterogeneity of CO2 and CH4 concentrations in the water and in ambient air above the water during a low water period in summer 2020. Overall, dissolved CH4 concentrations ranged over three orders of magnitude. Along the freshwater part of the transect, dissolved CH4 increased and weirs and harbors appeared to be hot spots of elevated CH4 concentrations both for the dissolved and atmospheric phase. We observed a longitudinal gradient of CO2 in the river which was closely linked to primary production. In the estuary and the marine part, dissolved CH4 concentrations of the transect were determined by the variability of temperature and salinity. Correlations with other water parameters revealed the complex regulation of dissolved CH4 concentrations along the freshwater-seawater continuum. For atmospheric CH4 above the North Sea, wind direction and wind speed proved to be crucial. Besides the typical diurnal fluctuations of atmospheric CO2 and CH4, an observed link between dissolved and atmospheric concentrations has to be further clarified

Influence of wind strength and direction on diffusive methane fluxes and atmospheric methane concentrations above the North Sea

Quantification of the diffusive methane fluxes between the coastal ocean and atmosphere is important to constrain the atmospheric methane budget. The determination of the fluxes in coastal waters is characterized by a high level of uncertainty. To improve the accuracy of the estimation of coastal methane fluxes, high temporal and spatial sampling frequencies of dissolved methane in seawater are required, as well as the quantification of atmospheric methane concentrations, wind speed and wind direction above the ocean. In most cases, these atmospheric data are obtained from land-based atmospheric and meteorological monitoring stations in the vicinity of the coastal ocean methane observations. In this study, we measured wind speed, wind direction and atmospheric methane directly on board three research vessels in the southern North Sea and compared the local and remote atmospheric and meteorological measurements on the quality of the flux data. In addition, we assessed the source of the atmospheric methane measured in the study area in the German Bight using air mass back-Trajectory assessments. The choice of the wind speed data source had a strong impact on the flux calculations. Fluxes based on wind data from nearby weather stations amounted to only 58 ± 34 % of values based on in situ data. Using in situ data, we calculated an average diffusive methane sea-To-Air flux of 221 ± 351 μmol m-2 d-1 (n Combining double low line 941) and 159 ± 444 μmol m-2 d-1 (n Combining double low line 3028) for our study area in September 2019 and 2020, respectively. The area-weighted diffusive flux for the entire area of Helgoland Bay (3.78 × 109 m2) was 836 ± 97 and 600 ± 111 kmol d-1 for September 2019 and 2020, respectively. Using the median value of the diffusive fluxes for these extrapolations resulted in much lower values compared to area-weighted extrapolations or mean-based extrapolations. In general, at high wind speeds, the surface water turbulence is enhanced, and the diffusive flux increases. However, this enhanced methane input is quickly diluted within the air mass. Hence, a significant correlation between the methane flux and the atmospheric concentration was observed only at wind speeds < 5 m s-1. The atmospheric methane concentration was mainly influenced by the wind direction, i.e., the origin of the transported air mass. Air masses coming from industrial regions resulted in elevated atmospheric methane concentrations, while air masses coming from the North Sea transported reduced methane levels. With our detailed study on the spatial distribution of methane fluxes we were able to provide a detailed and more realistic estimation of coastal methane fluxes

Methylomonas albis sp. nov. and Methylomonas fluvii sp. nov.: Two cold-adapted methanotrophs from the river Elbe and emended description of the species Methylovulum psychrotolerans

Three strains of methanotrophic bacteria (EbAT, EbBT and Eb1) were isolated from the River Elbe, Germany. These Gram-negative, rod-shaped or coccoid cells contain intracytoplasmic membranes perpendicular to the cell surface. Colonies and liquid cultures appeared bright-pink. The major cellular fatty acids were 12:0 and 14:0, in addition in Eb1 the FA 16:1ω5t was also dominant. Methane and methanol were utilized as sole carbon sources by EbBT and Eb1, while EbAT could not use methanol. All strains oxidize methane using the particulate methane monooxygenase. Both strains contain an additional soluble methane monooxygenase. The strains grew optimally at 15–25 °C and at pH 6 and 8. Based on 16S rRNA gene analysis recovered from the full genome, the phylogenetic position of EbAT is robustly outside any species clade with its closest relatives being Methylomonas sp. MK1 (98.24%) and Methylomonas sp. 11b (98.11%). Its closest type strain is Methylomonas methanica NCIMB11130 (97.91%). The 16S rRNA genes of EbBT are highly similar to Methylomonas methanica strains with Methylomonas methanica R-45371 as the closest relative (99.87% sequence identity). However, average nucleotide identity (ANI) and digital DNA-DNA-hybridization (dDDH) values reveal it as distinct species. The DNA G + C contents were 51.07 mol% and 51.5 mol% for EbAT and EbBT, and 50.7 mol% for Eb1, respectively. Strains EbAT and EbBT are representing two novel species within the genus Methylomonas. For strain EbAT we propose the name Methylomonas albis sp. nov (LMG 29958, JCM 32282) and for EbBT, we propose the name Methylomonas fluvii sp. nov (LMG 29959, JCM 32283). Eco-physiological descriptions for both strains are provided. Strain Eb1 (LMG 30323, JCM 32281) is a member of the species Methylovulum psychrotolerans. This genus is so far only represented by two isolates but Eb1 is the first isolate from a temperate environment; so, an emended description of the species is given

The challenge of sensor selection, long term-sensor operation and data evaluation in inter- -institutional long term monitoring projects - lessons learned in the MOSES project -

Measuring environmental variables over longer times in coastal marine environments is a challenge in regard to sensor maintenance and data processing of continuously produced comprehensive datasets. In the project “MOSES” (Modular Observation Solutions for Earth Systems), this procedure became even more complicated because seven large Helmholtz centers from the research field Earth and Environment (E&E) within the framework of the German Ministery of Educatiopn and Research (BMBF) work together to design and construct a large scale monitoring network across earth compartments to study the effects of short-term events on long term environmental trends. This requires the development of robust and standardized automated data acquisition and processing routines, to ensure reliable, accure and precise data. Here, the results of two intercomparison workshops on senor accuracy and precicion for selected environmental variables are presented. Environmental sensors which were to be used in MOSES campaigns on hydrological extremes (floods and draughts) in the Elbe catchment and the adjacent coastal areas in the North Sea in 2019 to 2020 were compared for selected parameters (temperature, salinity, chlorophyll-A, turbidity and methane) in the same experimentally controlled water body, assuming that all sensors provide comparable data. Results were analyzed with respect to individual sensor accuracy and precision related to an “assumed” real value as well as with respect to a cost versus accuracy/precision index for measuring specific environmental data. The results show, that accuracy and precision of sensors do not necessarily correlate with the price of the sensors and that low cost sensors may provide the same or even higher accuracy and precision values as even the highest price sensor types