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84 results for “Greenhouse gas emissions”
China's agricultural greenhouse gas emission intensity and its influencing factors
<p>This dataset includes the agricultural greenhouse gas emissions intensity of China and various factors that affect agricultural greenhouse gas emissions (agricultural patent intensity, agricultural per capita value added, urbanization rate, environmental investment intensity, and urban rural income gap.</p>
Private vehicles greenhouse gas emissions at street level for Berlin based on open data
<p>We estimated the annual average daily GHG emissions from individual motor traffic for the OSM road network in Berlin by combining the estimated Annual Average Daily Traffic Volume (AADTV) with respective emission factors. The AADTV was calculated by simulating car trips with the open routing engine Openrouteservice, weighted by activity functions based on statistics of the German Mobility Panel.</p>
Novel cropping system strategies in China can increase plant protein with higher economic value but lower greenhouse gas emissions and water use
<p> This database contains the average crop residue, manure nitrogen, manure organic carbon, net greenhouse gas emissions, and cropland area for 17 cropping systems at prefecture level during the period 2014-2018. In addition, it contained the changes of net greenhouse gas emissions caused by the optimization at prefecture level and province level.</p> <p> We also shared the key code for optimizing cropping systems at prefecture level and provided the all data. Users can run it the Matlab platform.</p>
Greenhouse gas emissions from drained organic forest soils data
<p>Compiled published peer-reviewed CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O data on drained organic forest soils in boreal and temperate zones.</p>
An approach to quantifying the key greenhouse gas emissions in California concrete production
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A unified approach to quantifying the key greenhouse gas emissions, air pollutant emissions, and water demand in concrete production
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Agroforestry carbon stocks and greenhouse gas emission rates in central Alberta, Canada
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Wetland drainage produces substantial greenhouse gas emissions in the Canadian Prairie Pothole Region
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Data from: Identifying environmental drivers of greenhouse gas emissions under warming and reduced rainfall in boreal-temperate forests
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Global land use change and its impact on greenhouse gas emissions
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Life-cycle greenhouse gas emissions in power generation using palm kernel shell
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Idiosyncratic phenology of greenhouse gas emissions in a Mediterranean reservoir
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Data for meta-analysis of the soil greenhouse gas emissions
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Hot spots and hot moments of greenhouse gas emissions in agricultural peatlands
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Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass-based biofuel production
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Data from: Compound- and context-dependent effects of antibiotics on greenhouse gas emissions from livestock
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The interplay between climate warming driven by greenhouse gas emissions and the ecotoxicological effects of microplastics: Insights from a meta-analysis
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Laboratory mesocosm data measuring the impact of bioturbation frequency on greenhouse gas emissions from reservoir sediments
Inland aquatic systems are major global contributors to the atmospheric carbon budget through greenhouse gas (GHG) emissions, although the amount and form of carbon released varies widely across and within systems. Bioturbation of aquatic sediments can impact biogeochemical conditions and physically release sediment-bound bubbles containing GHGs, but variation in the frequency of such disturbance may modify the rate and composition of resulting GHG emissions. We hypothesized that an intermediate bioturbation frequency would result in the greatest methane (CH4) releases due to mechanical release of trapped bubbles, while frequent disturbance would result in greater diffusive carbon dioxide (CO2) releases relative to CH4, due to increased aeration of the sediment. We tested this bioturbation frequency hypothesis using laboratory mesocosms containing homogenized reservoir sediment. We used mechanical disturbance to simulate bioturbation at 3, 7, 14, or 21-day intervals; a control treatment was undisturbed for the duration of the experiment. We measured GHG emission (ebullition and diffusion) rates. An intermediate frequency of disturbance (7 days) produced the highest total GHG emission rate, while the most frequent disturbance interval (3 days) and least frequent interval (0 days) reduced overall GHG emissions relative to weekly disturbance by 24% and 15%, respectively. These patterns were primarily driven by differences in CH4 ebullition. Contrary to our hypothesis, there was no relationship between disturbance frequency and diffusive CO2 emissions. For all disturbance treatments, the majority of ebullition occurred during disturbance events, suggesting mechanical release of entrapped bubbles is an important emission mechanism. The frequency of disturbance has variable effects on GHG emissions and may explain conflicting results in prior studies of bioturbation. Our study provides insight into bioturbation as a driver of within-system variation in GHG emissions and h
Data from: Reported U.S. Wild Game Consumption and Greenhouse Gas Emissions Savings
<p>These two tables present raw data utilized to calculated greenhouse gas savings associated with hunting within the US. Appendix I shows the estimated numbers of "big game" animals legally harvested in each state and the mean yield from each species. Appendix II shows total number of migratory waterfowl harvested in the US and the mean yield for each species. Both of these tables refer to the paper "Reported US Wild Game Consumption and Greenhouse Gas Emissions Savings" published in Human Dimensions of Wildlife.</p>
Energy consumption and greenhouse gas emissions data of activated carbon production using different biomass
<p>This dataset includes the energy consumption and Greenhouse Gas emissions data of activated carbon production using 73 different types of woody biomass.</p> <p>Understanding the environmental implications of activated carbon (AC) produced from diverse biomass feedstocks is critical for biomass screening and process optimization for sustainability. Many studies have developed Life Cycle Assessment (LCA) for biomass-derived AC. However, most of them either focused on individual biomass species with differing process conditions or compared multiple biomass feedstocks without investigating the impacts of feedstocks and process variations. Developing LCA for AC from diverse biomass is time-consuming and challenging due to the lack of process data (e.g., energy and mass balance).</p> <p>This study addresses these knowledge gaps by developing a modeling framework that integrates artificial neural network (ANN), a machine learning approach, and kinetic-based process simulation. The integrated framework is able to generate Life Cycle Inventory data of AC produced from 73 different types of woody biomass with 250 characterization data samples. The results show large variations in energy consumption and GHG emissions across different biomass species (43.4–277 MJ/kg AC and 3.96–22.0 kg CO<sub>2</sub>-eq/kg AC). The sensitivity analysis indicates that biomass composition (e.g., hydrogen and oxygen content) and process operational conditions (e.g., activation temperature) have large impacts on energy consumption and GHG emissions associated with AC production.</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.