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407 results for “greenhouse”
Lake Mendota Carbon and Greenhouse Gas Measurements at North Temperate Lakes LTER 2016
This original dataset contains carbon and greenhouse gas (GHG) data collected in Lake Mendota during the summer of 2016. Data were collected between 15 April 2016 and 14 November 2016 on both Lake Mendota and its surrounding streams—four major inflows and the primary outflow of Lake Mendota. The dataset is comprised of four linked tables, corresponding to carbon and GHG measurements on Lake Mendota (lake_weekly_carbon_ghg), weekly physico-chemical sonde casts on Lake Mendota (lake_weekly_ysi), ebullition rate estimates on Lake Mendota (lake_weekly_ebullition), and carbon and physico-chemical data from the four major inflows and primary outflow of Lake Mendota (stream_weekly_carbon_ysi). These data were used to explore the relationship between organic carbon dynamics and greenhouse gas production on a eutrophic lake. From these data, it is possible to estimate daily oxygen, methane, and carbon dioxide flux on Lake Mendota during the study time period. Additional methods and applications of this data can be found in J.A. Harts Masters Thesis, University of Wisconsin-Madison Center for Limnology, May 2017.
Time series of methane and carbon dioxide diffusive fluxes using an Ultraportable Greenhouse Gas Analyzer (UGGA) for Falling Creek Reservoir and Beaverdam Reservoir in southwestern Virginia, USA during 2018-2025
Diffusive fluxes of methane and carbon dioxide were measured using an Ultraportable Greenhouse Gas Analyzer (UGGA) at the surface of Falling Creek Reservoir (FCR) and Beaverdam Reservoir (BVR; Vinton, Virginia, USA). FCR and BVR are owned and operated by the Western Virginia Water Authority as drinking water sources for Roanoke, Virginia. The dataset consists of calculated diffusive fluxes of methane and carbon dioxide measured at the deepest site of the reservoir adjacent to the dam (2018–2025) and additional reservoir upstream sites in FCR (2018, 2023) and BVR (2022). In 2025, two littoral sites were measured at the northernmost wetland inflow to FCR. Measurements were collected approximately fortnightly in FCR throughout the summer stratified periods of 2018–2021 and 2023-2025, while measurements from BVR were only taken in 2018 and 2022-2024.
Greenhouse gas partial pressure (CO2, CH4, N2O) and environmental variables (physical, chemical, and biological) measured in urban ponds of Barcelona during summer and winter (2023-2024)
This dataset provides information on the partial pressure of greenhouse gases (CO₂, CH₄, and N₂O) measured in 41 artificial urban ponds—28 naturalized and 13 non-naturalized—using the headspace technique. Additionally, GPS coordinates, as well as physical, chemical, and biological variables for each pond, are included. Data were collected during the summer and winter seasons, during daytime. Furthermore, a subset of 16 ponds (8 naturalized and 8 non-naturalized) was also sampled at night in both seasons. All samples were taken from the water surface.
Soil dissolved organic matter and greenhouse gas fluxes from intact Delmarva Bay wetland soil cores during laboratory simulation of groundwater level rise
Wetlands in low-relief landscapes have dynamic terrestrial-aquatic interfaces as surface water and groundwater levels fluctuate seasonally and these variable water levels influence wetland carbon cycling. Seasonal changes in groundwater levels determine which soils are hydrologically connected to the wetland surface water-groundwater continuum and therefore which soils act as carbon sources. To quantify groundwater-mediated soil dissolved organic matter (DOM) and greenhouse gas (CO2 and CH4) fluxes, we performed a laboratory simulation of groundwater rise on intact soil cores. Soil cores were collected from four Delmarva Bay wetlands located in the low-relief landscape of the Delmarva Peninsula in the Mid-Atlantic United States. At each wetland, two cores (length = 60 cm, diameter = 10.2 cm) were collected: one from within the wetland basin and the second from the transitional zone near the edge of the wetland basin (total number of cores collected = 8). To characterize seasonal hydrologic conditions at each wetland site where intact soil cores were collected (e.g., mean water level, number of saturation events, duration of saturation), we used high frequency water level data collected in wetland center and upland groundwater monitoring wells. In the lab, cores were re-saturated with groundwater over 15 days and after cores were fully re-saturated, core water levels were maintained for an additional 25 days. Water levels in each head tank and soil core were manually recorded on sub-daily timesteps. Rhizon soil porewater samplers were installed at 8, 20, and 40 cm below the soil surface reflecting the expected depths of the O, A, and B soil horizons across the wetland sites. Source groundwater, soil porewater, and exfiltrated surface water samples were collected daily from the soil cores and analyzed for pH, ORP, and DOM concentration (dissolved organic carbon) and DOM composition (absorbance and fluorescence metrics). Discrete measurements of CO2 and CH4 fluxes were
Data associated with the FLooded Upland Dynamics EXperiment (FLUDEX), conducted at the IISD Experimental Lakes Area 1997 to 2003, investigating reservoir flooding impacts on ecosystems, particularly the release of mercury and greenhouse gases.
The data included in this repository were collected over the course of the FLooded Upland Dynamics Experiment (FLUDEX) conducted at the IISD Experimental Lakes Area (IISD-ELA) from 1997 to 2003. A plethora of data was collected over five years of flooding three upland reservoir sites, in order to examine the relationship between the amount of flooded, and thus decomposed, terrestrial organic matter and the production of methylmercury (MeHg), total mercury (THg), and greenhouse gases (GHGs) in the reservoirs. Findings from this experiment suggest that the amount of organic carbon stored in a flooded site does not directly influence the amount of THg, MeHg, and GHGs produced, but it does affect the persistence of mercury in the reservoir and food web. This version of the repository contains data collected on water chemistry, benthic invertebrate (chironomid) emergence, mercury and methylmercury concentrations in the water and food web, stable isotopes of carbon and nitrogen in emerging insects and zooplankton, and abundance and biomass of zooplankton, phytoplankton, and bacteria. This data package contains only some of the data from the FLUDEX project. IISD-ELA hopes to add more data in subsequent versions.
Lamprey River New Hampshire Greenhouse Gas Data, 2014-2023
The Lamprey River watershed, located in southeastern New Hampshire (USA), drains 554 km² of low elevation land before discharging into the Great Bay Estuary (Wymore and others 2021). The watershed is classified as suburban with mixed land-use that includes forests (73%), wetlands (10%), development (7%), and agriculture (NOAA Coastal Change Analysis Program 2016). We selected four distinct sites within the watershed to capture the dynamics of both tributaries and the mainstem, while accounting for variations in land use, land cover, and nutrient availability. Wednesday Hill Brook (WHB) is a 1st-order stream that drains a residential landscape and has the highest NO3 concentrations among the sites due to a high density of septic systems (Flint and McDowell 2015). Dowst Cate Forest (DCF) is a 2nd-order stream draining a headwater wetland and forested landscape and is characterized by the highest concentrations of dissolved organic carbon (DOC). The two main stem Lamprey River sites, LMP72 and LMP73, exhibit moderate concentrations of both DOC and NO3 and are located approximately 1 km apart. LMP72 is located at a low-head run-of-river dam while LMP73 is free-flowing water downstream of the reservoir. Our dataset includes weekly water chemistry and dissolved gas data collected from April 2014 through May 2023, except for DCF where data collection ended in 2021, resulting in a total of 1,179 observations across the four different sites.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra fertilized greenhouse simulation
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 25 years of tussock tundra under fertilized greenhouse conditions.
Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra greenhouse simulation
The Multiple Element Limitation (MEL) model is used to simulate the recovery of Alaskan arctic tussock tundra to thermal erosion features (TEFs) caused by permafrost thaw and mass wasting. TEFs could be significant to regional carbon (C) and nutrient budgets because permafrost soils contain large stocks of soil organic matter (SOM) and TEFs are expected to become more frequent as climate warms. These simulations deal only with recovery following TEF stabilization and do not address initial losses of C and nutrients during TEF formation. To capture the variability among and within TEFs, we simulate a range of post-stabilization conditions by varying the initial size of SOM pools and nutrient supply rates. This file contains the results for 25 years of tussock tundra under greenhouse conditions.
Greenhouse gas emissions from streams at North Temperate Lakes LTER 2012
Aquatic ecosystems can be important components of landscape carbon budgets. In lake-rich landscapes, streams may be important sources of greenhouse gases (CO2 and CH4) to the atmosphere in addition to lakes, but their source strength is poorly documented. The processes which control gas concentrations and emissions in these interconnected landscapes of lakes, streams and groundwater have not been adequately addressed. In this paper we use multiple datasets that vary in their spatial and temporal extent to investigate the carbon gas source strength of streams in a lake-rich landscape and to determine the roles of lakes and groundwater. We show that streams emit roughly the same mass of CO2 as regional lakes, and that stream CH4 emissions are an important component of the regional greenhouse gas balance.
Snow Manipulation Greenhouse Gas Measurements at South Sparkling and Trout Bog 2020-2021
To investigate the effect of a winter with decreased snow cover on greenhouse gas emissions, we experimentally removed snowfall from a small dystrophic lake in northern Wisconsin. As a comparative study, we were able to explore the role of light in under-ice gas dynamics and spring emissions in dimictic lakes. This dataset contains greenhouse gas and temperature/dissolved oxygen profile data collected on South Sparkling and Trout Bog during the winter of 2020 through the winter of 2021. Data were collected between 09 January 2020 and 13 April 2021 in the deep hole of both bogs. Dissolved greenhouse gas concentrations of carbon dioxide and methane were measured using the headspace equilibrium method.
UNFCCC country-submitted greenhouse gas emissions data until 2024-07-05
<p>Dataset containing all greenhouse gas emissions data submitted by countries under climate change convention (including CRF data) as published by the UNFCCC secretariat at 2024-07-05.</p>
GHG-depths: Greenhouse gas depth-profile data in 522 lakes worldwide
Lakes, ponds, and reservoirs (hereafter: “lakes”) are significant sources of the greenhouse gases carbon dioxide (CO2) and methane (CH4). Emissions of CO2 and CH4 from lakes are regulated in part by in-lake processes, including the production and storage of gases in the lower parts of the water column (bottom waters). However, while substantial efforts have been made to improve estimates of greenhouse gas emissions from lakes, limited data on gas concentrations along depth profiles have prevented the incorporation of bottom-water processes in global emission estimates. Here, we present GHG-depths: the largest existing dataset of depth-profile CO2 and CH4 measurements worldwide, including 522 lakes across 38 countries and all seven continents. These data include contributions from 45 research teams and 56 published studies, totaling 2558 discrete sampling events. As global change continues to alter biogeochemical cycling in lakes, these data can help improve mechanistic models to better predict greenhouse gas production and emission from lakes worldwide.
Summer water chemistry, high frequency sensors, zooplankton and benthic macroinvertebrate community composition, periphyton, fish, and macrophyte biomass, along with lake metabolism and greenhouse gas dynamics in six experimental ponds in central Iowa, USA (2020)
This data product contains physical, chemical, and biological data ranging from the minute to daily to weekly scale in six artificial ponds (400 square meter surface area, 2m depth) in central Iowa (USA) 2020. Ponds were paired into three sets of treatment and reference with treatment ponds receiving two nutrient pulses designed to increase ambient phosphorus concentrations ~ 3 - 5%. Nitrogen and phosphorus were added as NH4NO3 and H3PO4, respectively, at a 24:1 molar ratio. The first nutrient pulse occurred on Julian day of year (DOY) 176 corresponding to a 3% increase and the second nutrient pulse occurred on DOY 211 to a 5% increase. Each treatment-reference set had a different food web structure established ranging between low, intermediate, and high complexity based on trophic connectivity and food chain length. Added to this data package is a document titled "2020 Iowa State University Horticultural Farm Experimental Ponds Nutrient Addition Experiment". For experimental set up, context, and a summary table of the data tables archived herein with available variables please review this document. It is added to aid in successful interpretation and to increase ease-of-use. Please email Tyler Butts (tyler.james.butts@gmail.com) for any and all questions regarding context or use of this dataset!
Dissolved greenhouse gas concentrations derived from the NEON dissolved gases in surface water data product (DP1.20097.001)
This dataset contains partial pressure and molar concentration of dissolved carbon dioxide, methane, and nitrous oxide in 34 streams, rivers, and lakes calculated from headspace equilibration samples collected by the National Ecological Observatory Network (NEON). All input data were collected by NEON and is available on the NEON data portal at https://data.neonscience.org. Specifically, in situ dissolved gas concentrations were calculated from the air and headspace mixing ratios provided by the NEON Dissolved gases in surface water data product (DP1.20097.001), adjusted for sample and water temperature (DP1.20097.001, DP1.20264.001, DP1.20053.001), barometric pressure (DP1.20097.001, DP1.00004.001), and alkalinity (DP1.20093.001). The final set of inputs is found in the file, input_file, and the processing scripts are available at https://github.com/kellyaho/NEON-GHG-processing. The file, output_file, contains the raw outputs from running the input_file through the processing scripts. There are three outputs for each gas for each sample, one for each of three different pre-equilibration headspace mixing ratios (paired atmospheric samples, loess smoothing of atmospheric samples, and site-specific median). The file, GHG_final, contains the final dataset. This GHG_final uses the outputs from output_file calculated with paired atmospheric samples, and substitutes 0.01 μatm, 0.001 μM, 0.001 μatm, and 0.001 μM for any negative instances of pCH4, [CH4], pN2O, and [N2O], respectively. See methods for more detail. Please cite the NEON data inputs (listed below), in addition to this dataset, when using the data. NEON is sponsored by the National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON Program.
APEX beta greenhouse gas flux data from both the permafrost plateau area and the active thaw margin, from 2017 on
This dataset contains greenhouse gas flux data for the bog and permafrost plateau sites at the Alaskan Peatland Experiment (APEX) from 2017 on. Includes some environmentals, raw gas concentrations, and derived gas flux rates.
Greenhouse experiment (FCE) in April and August 2001: Responses of neotropical mangrove saplings to the combined effect of hydroperiod and salinity/Biomass
A greenhouse experiment was performed for 13.5 months to evaluate the effect of salinity and hydroperiod on seedling growth rates of 2 mangrove species( Laguncularia racemosa and Rizhophora mangle). Data analyses are currently being performed.
Greenhouse mixed culture experiment from August 2002 to April 2003 (FCE): Evaluate the effect of salinity and hydroperiod on interspecific mangrove seedlings growth rate (mixed culture) / Morphometric variables
A greenhouse experiment (mixed culture experiment) was performed for 8 months to evaluate the effect of salinity and hydroperiod on seedling growth rates of 2 mangrove species( Laguncularia racemosa and Rizhophora mangle). Data analyses are currently being performed.
warmXtrophic plant-soil interaction greenhouse experiment, Kellogg Biological Station, Hickory Corners, MI, 2021
Climate warming influences plant communities through both direct effects, such as changes in temperature, and indirect pathways mediated by changes in soil microbial communities. These microbe-mediated indirect effects may alter plant traits and ecosystem dynamics in ways that are often overlooked in studies focused solely on the direct impacts of warming. To test these microbe-mediated indirect effects, we used field-conditioned soil from a 7-year (2015-2021) warming experiment (warmXtrophic) in an early successional plant community in Hickory Corners, Michigan, USA at Michigan State University's Kellogg Biological Station Long-Term Ecological Research site. In a greenhouse during 2021, we assessed how warmed versus ambient soil inocula influenced plant growth and traits of two species: Trifolium pratense (red clover) and Phleum pratense (Timothy grass). We measured above, below, and total biomass, height, number of leaves, timing of germination, leaf % carbon and nitrogen, C:N ratio, specific leaf area (SLA), and greenness (a proxy for chlorophyll content). We also measured the timing of emergence of the cotyledon and first leaf for Trifolium pratense.
MAR2PROTECT - Coconut shell derived activated carbon for effective separation of greenhouse gases - DATASET
<p>The need for innovative and efficient adsorptive materials with enhanced structural characteristics that facilitate the selective capture of greenhouse gases (GHGs) is critical. Porosity and surface area play an important role in the adsorptive capture and separation of GHGs, enabling the design of processes that reduce GHGs emissions. This study shows how residual coconut shell (CS) biomass can be reused for the design of novel biomaterials (CS-CO<sub>2</sub>, CS-ZnCl<sub>2</sub>) with structural characteristics that promote the selective adsorption of GHGs. Additionally, the results are compared with those obtained with activated carbon monoliths (ACM) and a Metal-Organic Framework (MOF Fe-BTC) to understand the impact of different porous solid matrices on adsorptive GHG capture. In this context, the adsorption performance of difluoromethane (R-32), pentafluoroethane (R-125), 1,1,1,1-tetrafluoroethane (R-134a), 1,1,1,1-trifluoroethane (R-143a), carbon dioxide (CO<sub>2</sub>), and methane (CH<sub>4</sub>) on CS-CO<sub>2</sub>, CS-ZnCl<sub>2</sub>, ACM and Fe-BTC were measured by gravimetry at 283.15 K, 303.15 K and 323.15 K. The experimental data are correlated using the dual-site Langmuir adsorption model, and the selectivities of the commercial mixtures R-410A, R-407C, R-404A and CO<sub>2</sub>/CH<sub>4</sub> are calculated using the Ideal Adsorption Solution theory (IAST). CS-ZnCl<sub>2</sub> has a higher selectivity for R-125 over R-32 in the separation of R-410A at low pressure, and also a higher selectivity for R-407C due to its larger pore volume. In the separation of the R-404A refrigerant blend, CS-CO<sub>2</sub> adsorbs predominantly R-134a and R-143a over R-125. Finally, the ACM material preferentially adsorbs CO<sub>2</sub> over CH<sub>4</sub>, owing to its large and elongated micropores that favour the adsorption of the smaller molecule. This study introduces novel and innovative materials to enhance the separation of GHGs mixtures, contributing to a reduction in their emissions.</p>
COMPAIR carbon footprint calculations and greenhouse gas emissions reduction scenarios
<p>Citizens' carbon footprint calculation results and citizen-created scenarios on how Greenhouse Gas emissions can be reduced by 55% by 2030 are available that were gathered as part of the <a href="https://cordis.europa.eu/project/id/101036563">EU Horizon2020 COMPAIR project</a> in Europe. The pilot cities/regions are Berlin, Athens, Sofia, Plovdiv, and Flanders.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.