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18 results for “ebullition”
Ebullitive methane emissions from oxygenated wetland streams at North Temperate Lakes LTER 2013
Stream and river carbon dioxide emissions are an important component of the global carbon cycle. Methane emissions from streams could also contribute to regional or global greenhouse gas cycling, but there are relatively few data regarding stream and river methane emissions. Furthermore, the available data do not typically include the ebullitive (bubble-mediated) pathway, instead focusing on emission of dissolved methane by diffusion or convection. Here, we show the importance of ebullitive methane emissions from small streams in the regional greenhouse gas balance of a lake and wetland-dominated landscape in temperate North America and identify the origin of the methane emitted from these well-oxygenated streams. Stream methane flux densities from this landscape tended to exceed those of nearby wetland diffusive fluxes as well as average global wetland ebullitive fluxes. Total stream ebullitive methane flux at the regional scale (103 Mg C yr-1; over 6400 km2) was of the same magnitude as diffusive methane flux previously documented at the same scale. Organic-rich stream sediments had the highest rates of bubble release and higher enrichment of methane in bubbles, but glacial sand sediments also exhibited high bubble emissions relative to other studied environments. Our results from a database of groundwater chemistry support the hypothesis that methane in bubbles is produced in anoxic near-stream sediment porewaters, and not in deeper, oxygenated groundwaters. Methane interacts with other key elemental cycles such as nitrogen, oxygen, and sulfur, which has implications for ecosystem changes such as drought and increased nutrient loading. Our results support the contention that streams, particularly those draining wetland landscapes of the northern hemisphere, are an important component of the global methane cycle.
PIE LTER stream chemistry characteristics studied for methane ebullition at four headwater streams in Massachusetts and New Hampshire.
Sediment, stream, and canopy characteristics were measured in four headwater streams in Massachusetts and New Hampshire associated with methane ebullition monitoring. Canopy cover, water depth, sediment organic matter content, the percent sediment less than 2mm in diameter, sediment depth, sediment percent carbon, and sediment percent nitrogen were measured. Other files to reference: WAT-Stream-Ebullition
Methane ebullition and diffusion rates, turbulence, water temperature, and water depth data from Falling Creek Reservoir (Virginia, USA) in the ice-free period during 2016-2019
This dataset includes weekly and subweekly methane ebullition and diffusion rates collected from March through November in 2016, 2017, 2018, and 2019 in Falling Creek Reservoir (FCR), a drinking water reservoir owned and managed by the Western Virginia Water Authority and located in Vinton, Virginia, USA. In 2016, ebullition rates were measured at four near-shore sites along a longitudinal gradient in FCR that included four replicate locations within each site, for a total of 16 sites in the reservoir. In 2017, methane emission rates and five different potential environmental driver variables (water temperature, wind speed, pressure, turbulence, primary production) were measured at five longitudinal transects that included four replicate sites per transect, for a total of 20 sites in the reservoir. In 2018, ebullition was measured at the same five longitudinal transects but with two replicate sites per transect, for a total of 10 sites. In 2019, ebullition was only measured at the furthest upstream transect monitored in 2017-2018, with four replicate sites within that transect. The dataset consists of four tables: 1) weekly methane ebullition and diffusion rates and the water depths at each of the 24 unique monitoring sites; 2) 10-minute resolution sediment-water interface and surface water temperatures from 16 sites in 2017; 3) weekly sediment-water interface and surface turbulence at the four transects in 2017; and 4) geographical coordinates of each of the 24 sites in the reservoir.
PIE LTER time series of methane, CO2 and N2O ebullition measurements at four headwater streams in Massachusetts and New Hampshire.
Methane ebullition was monitored at four headwater streams during 2018 and 2019. Stationary bubble traps were deployed from approximately May through October. CC and SB were monitored in 2018 and 2019, while DB and CB were only monitored in 2019. 12 traps were deployed at CC, SB, and DB, and 9 traps were deployed at CB. The concentration measured in the emitted gas was multiplied by the volume measured in a trap to calculated the total methane flux via ebullition. The traps were visited at least once weekly. The mean, median, minimum, and maximum rate of ebullition across all traps at a site over a two week period are listed here. Relevant publications: Robison, A.L. (2021) Carbon emissions from streams and river: Integrating methane emission pathways and storm carbon dioxide emissions into stream and river carbon balances. Doctoral Dissertation. University of New Hampshire. Robison, A.L., W.M. Wollheim, B. Turek, C. Bova, C Snay, & R.K. Varner (in review). Spatial and temporal heterogeneity of methane ebullition in lowland headwater streams. Limnology and Oceanography.
Raw data sets for: A simple calculation algorithm to seperate high-resolution CH4 flux measurements into ebullition- and diffusion derived components (AMT)
<p>Raw data sets for the research article "A simple calculation algorithm to seperate high-resolution CH4 flux measurements into ebullition- and diffusion derived components", published in "Atmospheric Measurment Techniques" (AMT). Data sets include raw data sets for the field and laboratory study, as well as calculated CH4 fluxes (field).</p>
A temporally consistent spatial gradient in methane ebullition from a eutrophic lake
<p>CH4 ebullition rates from lake Alstasjö (<a href="../api/records/11205773/draft/files/CH4Ebullition.xlsx/content" target="_blank" rel="noopener noreferrer">CH4Ebullition.xlsx</a>)</p> <p>CH4 ebullition rates from lake Alstasjö related to sediment temperature (<a href="../api/records/11205773/draft/files/CH4_Ebullition_Site_SedT.csv/content" target="_blank" rel="noopener noreferrer">CH4_Ebullition_Site_SedT.csv</a>)</p> <p>CH4 and gas ebullition rates and sedment characteristics (<a href="../api/records/11205773/draft/files/CH4_GS_update5.csv/content" target="_blank" rel="noopener noreferrer">CH4_GS_update5.csv</a>)</p> <p>Supplementary information <a href="../api/records/11205773/draft/files/SupportingInfo.pdf/content" target="_blank" rel="noopener noreferrer">SupportingInfo.pdf</a> </p> <p>Oxygen levels at lake Alstasjö between 2020-2021 (<a href="../api/records/11205773/draft/files/O2_Alsta_DailyMean.csv/content" target="_blank" rel="noopener noreferrer">O2_Alsta_DailyMean.csv</a>)</p> <p>Sediment dating from sediment cores collected at Alstasjö near bubble traps (<a href="../api/records/11205773/draft/files/CH4_SedimentDating.csv/content" target="_blank" rel="noopener noreferrer">CH4_SedimentDating.csv</a> and </p> <p><a href="../api/records/11205773/draft/files/CH4_SedimentDating_Cs.csv/content" target="_blank" rel="noopener noreferrer">CH4_SedimentDating_Cs.csv</a>)</p> <p>Results of lake Alstasjö thermal dynamics using lake analyzer (<a href="../api/records/11205773/draft/files/results_rLakeAnalyzer_Alsta.csv/content" target="_blank" rel="noopener noreferrer">results_rLakeAnalyzer_Alsta.csv</a>)</p> <p>Water level and discharge from Alstasjö (<a href="../api/records/11205773/draft/files/WaterLevelvsDischarge.xlsx/content" target="_blank" rel="noopener noreferrer">WaterLevelvsDischarge.xlsx</a>)</p>
Ebullition drives high methane emissions from a eutrophic coastal basin
<p>Dataset used in the article: "Ebullition drives high methane emissions from a eutrophic coastal basin".</p>
Subsurface redox interactions regulate ebullitive methane flux in heterogeneous Mississippi River deltaic wetland
<p>This dataset is model outputs archive from a model study about 'Subsurface redox interactions regulate ebullitive methane flux in heterogeneous Mississippi River deltaic wetland' (manuscript is Under Review). Plotting scripts are also included in this data file. There are four model results. 'Ebull' model output are ebullition flux, 'Jswi' model output are diffusion flux across soil-water interface, and 'Methane' files are porewater concentration results in each soil layers, and 'LtranR' model outputs for redox species exchange rates across different soil layers. The model source codes can be found at <a href="https://zenodo.org/record/8084441">https://zenodo.org/record/8084441</a> and <a href="https://zenodo.org/record/8087566">https://zenodo.org/record/8087566</a>.</p>
Date set for the manuscript: Exploring the temporal dynamics of methane ebullition in a subtropical freshwater reservoir
<p>The dataset supports the findings of the manuscript entitled ‘Exploring the Temporal Dynamics of Methane Ebullition in a Subtropical Freshwater Reservoir’. The results of the manuscript are based on continuous in-situ measurements conducted at Passaúna Reservoir, located in the southern part of Brazil (South America). The monitoring was carried out from 2017 to 2020, during which a comprehensive set of environmental variables was obtained from various studies. The primary objective of the manuscript was to comprehend the temporal dynamics of ebullition flux in the reservoir. Therefore, time series data of ebullition and relevant environmental variables were analyzed across different time scales, ranging from minutes to daily resolutions. Statistical and data driven models were tested to predict ebullition at varying time scales, considering the influence of environmental variables. The findings are discussed in the manuscript.</p> <p>Here, xlsx files and Matlab scripts are provided. The xlsx files contain time series data for environmental variables ('Environmental_Variables_TimeSeries') and ebullition flux ('Ebullition_Flux_TimeSeries'). Separate sheets were utilized for different time intervals, namely 5 minutes (dt=5min), 10 minutes (dt=10min), 1 hour (dt=1hr), and 1 day (dt=1d). Explanations and units are provided within the column labels, while 'NaN' denotes missing data.</p> <p>Matlab scripts for all the empirical models that were tested, as outlined in the manuscript's supporting information (Tables S1 and S2), have been made available (detailed in the following table). These scripts were developed using MatLab R2023a.</p> <table> <tbody> <tr> <td> <p>File (.m)</p> </td> <td> <p>Description</p> </td> </tr> <tr> <td> <p><strong>Main scripts</strong></p> </td> </tr> <tr> <td> <p>TableS1_Empirical_Models_Literature</p> </td> <td> <p>Empirical models from the literature tested. (Table S1 in the manuscript)</p> </td> </tr> <tr> <td> <p>TableS2_FirstPart_Reffited_Models</p> </td> <td> <p>Empirical models from the literature refitted. (Table S2 in the manuscript)</p> </td> </tr> <tr> <td> <p>TableS2_SecondPart_New_Models</p> </td> <td> <p>New empirical models implemented. (Table S2 in the manuscript)</p> </td> </tr> <tr> <td> <p>TableS2_SecondPart_New_Models_GAM_Timescales</p> </td> <td> <p>Generalized additive models (GAM) applied to predict ebullition at different timescales. (Table S2 in the manuscript).</p> </td> </tr> <tr> <td> <p>PredictedR2_GAM_models</p> </td> <td> <p>Calculate the predicted R-squared for GAM.</p> </td> </tr> <tr> <td> <p><strong>Functions (need for the main scripts)</strong></p> </td> </tr> <tr> <td> <p>load_TimeSeries</p> </td> <td> <p>Import time series of environmental variables from excel sheets into MatLab.</p> </td> </tr> <tr> <td> <p>load_EbullitionTS</p> </td> <td> <p>Import time series of ebullition from excel sheets into MatLab.</p> </td> </tr> <tr> <td> <p>units_description</p> </td> <td> <p>Description containing units of the variables.</p> </td> </tr> <tr> <td> <p>Bin_xdata</p> </td> <td> <p>Creates data binning of X and Y based on X data.</p> </td> </tr> <tr> <td> <p>RelativeError</p> </td> <td> <p>Calculate the relative error of accumulated flux between measured and simulated.</p> </td> </tr> <tr> <td> <p>ANN5Neurons_Retrained_Deshmukh2014</p> </td> <td> <p>Trained Artificial Neural Network based on the ANN proposed by Deshmukh et al. (2014).</p> </td> </tr> <tr> <td> <p>ANN_Passauna_20Neurons</p> </td> <td> <p>Trained Artificial Neural Network with the addition of more environmental variables.</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Financial support</strong></p> <p>The field measurements were financed by the German Federal Ministry of Education and Research (BMBF, Grant 02WGR1431A), in the framework of the research project MuDak-WRM (https://www.mudak-wrm.kit.edu). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001. Tobias Bleninger received productivity stipend from the National Council for Scientific and Technological Development (CNPq, grant no. 312211/2020-1, call no. 09/2020). Michael Männich received productivity stipend from the National Council for Scientific and Technological Development (CNPq, grant no. 308744/2021-7, call no. 04/2021). Andreas Lorke received financial support from the German Research Foundation (DFG, grant number LO1150/16-1).</p>
Atmospheric pressure influencing ebullition and turbidity
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Data from: Seasonal and spatial dynamics of gas ebullition in a temperate water-storage reservoir
Gas ebullition of river impoundments plays an increasingly significant role, particularly in transporting methane CH4 from their sediments to the atmosphere, and contributing to the global carbon budget and global warming. Quantifying stochastic and episodic nature of gas ebullition is complicated especially when conventionally conducted by using coverage-limited gas traps. Current knowledge of seasonality in a reservoir's gas ebullition is lacking in the literature. For this reason, advanced acoustic surveying was intensively applied to determine spatiotemporal distributions of gas ebullition in a European water-storage reservoir for two years. Additionally, the sampling was accompanied with gas collecting for analyzing gas composition. The gas released from the reservoir was primarily composed of CH4 (on average 52%, up to 94%). The longitudinal distribution of gas ebullition was mainly determined by a proximity to the river inflow as a source of organic matter. A magnitude of ebullitive fluxes within the reservoir varied up to 1,300 mL m-2 d-1(30 mmol CH4 m-2 d-1). The most significant period of ebullition has turned out to be in fall, on average reaching a sevenfold ebullitive flux (70 mL m-2 d-1, 1.6 mmol CH4 m-2 d-1) higher than in the rest of the season. A substantial contribution to the fall peak was induced by an expansion of gas ebullition into greater depths, covering two thirds of the reservoir in late fall. The study demonstrates that the ebullitive fluxes of the temperate water storage reservoir were correlated to season, depth, and inflow proximity.
Dataset for "Technical Note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models "
<p>This record contains data used in Peltola et al. (2018): Technical Note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models, Biogeosciences.</p> <p>The record contains model input data, as well as CH<sub>4</sub> flux data used to validate the modelling results.</p> <p>Please see the read me file for more information.</p> <p>For further information contact Olli Peltola (olli.peltola@helsinki.fi)</p>
Supplemental Dataset for paper: Methane ebullition from subtropical peat: testing an ebullition model reveals the importance of pore structure
<p>A dataset requested for publication of Journal Article, "<strong>Methane ebullition from subtropical peat: testing an ebullition model reveals the importance of pore structure"</strong></p>
Data from: Seasonal and spatial dynamics of gas ebullition in a temperate water-storage reservoir
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Sedimentation of autochthonous labile lipids facilitates methane ebullition
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Methane ebullition fluxes from hydropower reservoirs: dataset
<p>Dataset relevant to the article: Diel pumped-storage operation minimizes methane ebullition fluxes from hydropower reservoirs. DOI: 10.1029/2020WR027221</p>
ABoVE: Methane Ebullition Hotspots in Frozen Lakes near Fairbanks, Alaska, Oct 2014
This dataset includes maps of the locations and number of methane ebullition hotspots in 15 frozen lakes in the southern portion of the Goldstream Valley and the surrounding landscape just north of Fairbanks, Alaska, USA. Hotspots were identified from early winter high resolution aerial photographs acquired three days after lake-ice formation in October 2014. Hotspot ebullition seeps are defined as point-sources of high ebullition that release methane from lake sediments year-round. High rates of bubbling impede ice formation. In early winter, bubbling leads to dark, round open holes in lake ice which were visible in the aerial photos. This project investigated the role of theromkarst lakes in thawing of permafrost and mobilization of organic carbon in frozen soils.
ABoVE: SAR-based Methane Ebullition Flux from Lakes, Five Regions, Alaska, 2007-2010
This dataset provides Synthetic Aperture Radar (SAR) estimates of lake-source methane ebullition flux in mg CH4/m2/d for thousands of lakes in five regions across Alaska. The study regions include the Atqasuk, Barrow Peninsula, Fairbanks, northern Seward Peninsula, and Toolik. L-band SAR backscatter values for early winter lake ice scenes were collected from 2007 to 2010 over 5,143 lakes using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) instrument on the Advanced Land Observing Satellite (ALOS-1) satellite. The backscatter data were combined with field measurements of methane ebullition from 48 study lakes across the five regions to obtain a volumetric flux estimate for each lake. Mean methane gas-fractions from each region were applied to the SAR-based volumetric fluxes to obtain an estimate of methane ebullition mass flux per lake. The data files contain lake perimeters and the lake-specific attributes of lake area, SAR backscatter values and standard errors, volumetric flux with standard errors, mean percent of methane from gas samples, and methane ebullition mass flux.
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