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description Publicationkeyboard_double_arrow_right Article , Journal 2020Publisher:Elsevier BV Hee Chul Woo; Hoang Vu Ly; Hoang Vu Ly; Seung-Soo Kim; Jeong Woo Park; Jinsoo Kim; Hyun Tae Hwang;Abstract Bamboo has been considered a potential feedstock of energy for the future. It can be subjected to the pyrolysis for biofuels production. The thermogravimetric analysis (TGA) combined with differential thermogravimetric analysis (DTG) for bamboo was carried out prior to pyrolysis. The thermal degradation of bamboo was mainly between 230 and 420 °C. The conventional pyrolysis of bamboo was investigated in a bubbling fluidized-bed reactor using silica sand. The product distribution and composition of pyrolysis bio-oil were dependent on biomass component and operating conditions such as pyrolysis temperature, fluidization velocity, and particle size of biomass. The fractional catalytic pyrolysis of bamboo was also studied to upgrade the pyrolysis vapor, using HZSM-5 and red mud. The highest yield of bio-oil was 54.03 wt% compared to 49.14 wt% and 50.34 wt% of HZSM-5 and red mud catalyst, respectively. In the red mud catalytic pyrolysis, the oxygen content was rejected from pyrolysis vapor mostly via decarboxylation to produce more CO2 than CO; in contrast, for the HZSM-5 catalytic pyrolysis, the production of CO through decarbonylation was more favored than CO2. The main composition of catalytic pyrolysis bio-oil was 4-vinylphenol, which was employed as a raw material source to synthesize valuable material for energy storage.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2019.10.141&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 69 citations 69 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2019.10.141&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Report , Other literature type 2007 United StatesPublisher:Office of Scientific and Technical Information (OSTI) Authors: Agonafer, Dr. Dereje;doi: 10.2172/928422
The work described in this report was performed under the direction of the Industrial Assessment Center (IAC) at University of Texas at Arlington. The IAC at The University of Texas at Arlington is managed by Rutgers University under agreement with the United States Department of Energy Office of Industrial Technology, which financially supports the program. The objective of the IAC is to identify, evaluate, and recommend, through analysis of an industrial plant’s operations, opportunities to conserve energy and prevent pollution, thereby reducing the associated costs. IAC team members visit and survey the plant. Based upon observations made in the plant, preventive/corrective actions are recommended. At all times we try to offer specific and quantitative recommendations of cost savings, energy conservation, and pollution prevention to the plants we serve.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2172/928422&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2172/928422&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022Publisher:MDPI AG Ahmad Soltanzadeh; Mohsen Mahdinia; Alireza Omidi Oskouei; Ehsan Jafarinia; Esmaeil Zarei; Mohsen Sadeghi-Yarandi;doi: 10.3390/su142416555
Due to their unique nature, construction projects are considered one of the world’s most hazardous and incident-prone industrial sectors. The present study aimed to analyze health, safety and environmental (HSE) risks relating to construction projects based on the project management body of knowledge (PMBOK) and sustainability approach. This study was conducted with the participation of 30 experts, using the semi-quantitative risk assessment technique, in nine areas of the project management’s body of knowledge, based on the fuzzy analytic hierarchy process. Risk, in this study, was estimated using a two-dimensional matrix of incident probability and severity, each of which has four sub-parameters. The HSE risks pertaining to each of the nine areas of PMBOK were identified. After that, the two dimensions of risk, including incident probability and severity, were measured. Thirty-seven risk sources associated with nine areas of the PMBOK were identified. Risk analysis revealed that 20 sources were at an unacceptable risk level, and 17 risks were at a tolerable risk level. Identifying HSE-related risk sources in accordance with the nine areas of PMBOK, and using FAHP to assess the risk of these hazards in construction projects, can lead to a more realistic estimate of risk in construction projects. The presented method in the current study can create a novel perspective in terms of the construction industry’s risk management and assessment.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su142416555&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 10 citations 10 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su142416555&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euapps Other research productkeyboard_double_arrow_right Other ORP type 2021 United StatesPublisher:World Bank, Washington, DC Authors: World Bank Group;handle: 10986/34971
The country’s unique philosophy is expressed by Bhutan’s Gross National Happiness (GNH) as the guiding principle of development. Bhutan is at a crossroads: It can maintain the current pattern of development—with rising inequality—or develop a vibrant private sector to generate jobs and diversify the economy, building resilience to future external shocks. The overarching priority of this Country Partnership Framework (CPF) is job creation. This CPF presents an integrated framework of WBG support to help Bhutan achieve inclusive and sustainable development through private sector–led job creation.
Open Knowledge Repos... arrow_drop_down Open Knowledge RepositoryOther ORP type . 2021License: CC BYData sources: Open Knowledge Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10986/34971&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert Open Knowledge Repos... arrow_drop_down Open Knowledge RepositoryOther ORP type . 2021License: CC BYData sources: Open Knowledge Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10986/34971&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019Publisher:Wiley Lídia Cantacorps; Lídia Cantacorps; Rainer Spanagel; Olga Valverde; Shoupeng Wei; Ainhoa Bilbao; Sarah Leixner;doi: 10.1111/adb.12784
pmid: 31237390
AbstractThe co‐occurrence of chronic pain and alcohol use disorders (AUDs) involves complex interactions between genetic and neurophysiological aspects, and the research has reported mixed findings when they both co‐occur. There is also an indication of a gender‐dependent effect; males are more likely to use alcohol to cope with chronic pain problems than females. Recently, a new conceptualization has emerged, proposing that the negative affective component of pain drives and maintains alcohol‐related behaviors. We studied in a longitudinal fashion alterations in alcohol drinking patterns and pain thresholds in a mouse model of chronic neuropathic pain in a sex‐dependent manner. Following partial denervation (spared nerve injury [SNI]), stimulus‐evoked pain responses were measured before chronic alcohol consumption, during drinking, during a deprivation phase, and following an episode of excessive drinking. During the course of alcohol drinking, we observed pronounced sex differences in pain thresholds. Male mice showed a strong increase in pain thresholds, suggesting an analgesic effect induced by alcohol over time, an effect that was not observed in female mice. SNI mice did not differ from sham‐operated controls in baseline alcohol consumption. However, following a deprivation phase and the reintroduction of ethanol, male SNI mice but not female mice showed more pronounced excessive drinking than controls. Finally, we observed decreased central ethanol sensitivity in male SNI mice but not in females. Together with our finding, that ethanol is able to decrease a pain‐induced negative affective memory we come to following conclusion. We propose that a lower sensitivity to the intoxicating effects of alcohol together with the ability of alcohol to reduce the negative affective component of pain may explain the higher co‐occurrence of AUD in male chronic pain patients.
Addiction Biology arrow_drop_down Addiction BiologyArticle . 2019 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routesbronze 13 citations 13 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Addiction Biology arrow_drop_down Addiction BiologyArticle . 2019 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/adb.12784&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:NSF Arctic Data Center Atwood, Trisha; Beard, Karen; Waring, Bonnie; Adkins, Jaron; Saunders, Taylor;doi: 10.18739/a2cc0tv7w
Global change drivers that modify the quality and quantity of litter inputs to soil affect greenhouse gas fluxes, and thereby constitute a feedback to climate change. Carbon cycling in the Yukon-Kuskokwim (Y-K) River Delta, a subarctic wetland system, is influenced by landscape variations in litter quality and quantity generated by herbivores (migratory birds) that create ‘grazing lawns’ of short stature, nitrogen-rich vegetation. To identify the mechanisms by which these changes in litter inputs affect soil carbon balance, we independently manipulated qualities and quantities of litter representative of levels found in the Y-K Delta in a fully factorial microcosm experiment. We measured carbon dioxide (CO2) fluxes from these microcosms weekly. To help us identify how litter inputs influenced greenhouse gas fluxes, we sequenced soil fungal and bacterial communities, and measured soil microbial biomass carbon, dissolved carbon, inorganic nitrogen, and enzyme activity. We found that positive correlations between litter input quantity and CO2 flux were dependent upon litter type, due to differences in litter stoichiometry and changes to the structure of decomposer communities, especially the soil fungi. These community shifts were particularly pronounced when litter was added in the form of herbivore feces, and in litter input treatments that induced nitrogen limitation (i.e., senesced litter). The sensitivity of carbon cycling to litter quality and quantity in this system demonstrates that herbivores can strongly impact greenhouse gas fluxes through their influence on plant growth and tissue chemistry.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18739/a2cc0tv7w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18739/a2cc0tv7w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 12 Jan 2023Publisher:Dryad Floess, Emily; Grieshop, Andrew; Puzzolo, Elisa; Pope, Daniel; Leach, Nicholas; Smith, Christopher J.; Gill-Wiehl, Annelise; Landesman, Katherine; Bailis, Robert;Nearly three billion people in low- and middle-income countries (LMICs) rely on polluting fuels, resulting in millions of avoidable deaths annually. Polluting fuels also emit short-lived climate forcers and greenhouse gases (GHGs). Liquefied petroleum gas (LPG) and grid-based electricity are scalable alternatives to polluting fuels but have raised climate and health concerns. Here, we compare emissions and climate impacts of a business-as-usual household cooking fuel trajectory to four large-scale transitions to gas and/or grid electricity in 77 LMICs. We account for upstream and end-use emissions from gas and electric cooking, assuming electrical grids evolve according to the 2022 World Energy Outlook’s “Stated Policies” Scenario. We input the emissions into a reduced-complexity climate model to estimate radiative forcing and temperature changes associated with each scenario. We find full transitions to LPG and/or electricity decrease emissions from both well-mixed GHG and short-lived climate forcers, resulting in a roughly 5 millikelvin global temperature reduction by 2040. Transitions to LPG and/or electricity also reduce annual emissions of PM2.5 by over 6 Mt (99%) by 2040, which would substantially lower health risks from Household Air Pollution. Primary input data was collected from the following sources: Baseline household fuel choices - WHO household energy database (https://www.nature.com/articles/s41467-021-26036-x) End-use emissions - US EPA lifecycle assessment of household fuels (https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=339679&Lab=NRMRL&simplesearch=0&showcriteria=2&sortby=pubDate&timstype=Published+Report&datebeginpublishedpresented) Upstream emissions - Argonne National Labs GREET Model (https://greet.es.anl.gov/index.php) Current and future population estimates - UNECA (http://data.un.org/Explorer.aspx?d=EDATA) Input data was processed by defining household fuel choice scenarios, estimating national household fuel consumption based on these scenarios, and applying fuel-specific emission factors to create country-specific emission pathways. These emission pathways were input into the FaIR model (https://zenodo.org/record/5513022#.Yt_jfHbMLb0) which generated additional data for each scenario including time series of pollution concentrations, radiative forcing, and temperature changes. All data is provided in CSV format. Nothing proprietary is required.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5061/dryad.jq2bvq8d9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Top 10% influence Average impulse Average Powered by BIP!
visibility 3visibility views 3 download downloads 2 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5061/dryad.jq2bvq8d9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Embargo end date: 30 Jul 2019Publisher:Harvard Dataverse Authors: Scarpelli, Tia R.; Jacob, Daniel J.;doi: 10.7910/dvn/hh4eum
This is the Global Fuel Exploitation Inventory (GFEI) which provides a 0.1 x 0.1 degree grid of methane emissions of fugitive emissions related to oil, gas, and coal activities (IPCC Sector 1B1 and 1B2). Subsector emissions are provided from exploration to distribution of the resource. The inventory emissions are based on individual country reports submitted in accordance with the United Nations Framework Convention on Climate Change (UNFCCC). For those countries that do not report we estimate emissions following IPCC methods. Emissions are allocated to infrastructure locations including mines, wells, pipelines, compressor stations, storage facilities, processing plants, and refineries. This version of the inventory (GFEI v3) inventory is for 2020 and presents an update of GFEI v2 and v1 which were for 2019 and 2016, respectively. Emission grids are also available for 2010-2019. In GFEI v3, for each sector (oil, gas, coal) and subsector (exploration, production, etc.) there are emission grids. File names are in netcdf format and should start with "Global_Fuel_Exploitation_Inventory_v3_2020_" followed by the sector or subsector name. Please contact us if you would like emissions for an alternate year. We will also make input data and code available upon reasonable request.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.7910/dvn/hh4eum&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 08 Jun 2022Publisher:Dryad Brady, Hannah; Barsotti, Gabrielle; Davis, Jordan; Norris, Carly; Shaphran, Eric;doi: 10.25349/d9rg87
In recent years, there has been increased attention and focus from the public on the environmental impact of professional sports organizations. Significant opportunities exist for Major League Baseball (MLB) teams to both reduce their own environmental footprint, and that of their fans, through sustainability initiatives. Despite stadiums using upwards of ten million gallons of water per year and having the same energy needs as a small city, no MLB team has completed a public-facing quantification of their total environmental footprint. This project calculated the carbon footprint and water consumption of the Tampa Bay Rays for the 2019 regular season. We analyzed Scope 1, 2, and 3 GHG emissions to identify hotspots within the Rays’ operations, supply chains, and transportation. Fan transportation was found to be the largest source of GHGs, followed by food production for concessions. The cooling tower and restrooms were identified as the largest sources of onsite water usage. We created a repository of best practices as a resource for stadium managers that includes strategies to reduce GHGs and water use coupled with scenario analyses estimating potential reductions. The following recommendations are highlighted as the largest reduction opportunities: (1) prioritizing fan engagement to switch to more sustainable modes of transportation, and (2) offering and highlighting more vegetarian options at concessions. To further reduce emissions and water usage, MLB teams should prioritize sub-metering electricity and water lines and installing more efficient equipment. Data was provided by the Tampa Bay Rays and collected at Tropicana Field (where the Rays play) by Jordan Davis during the summer of 2021.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25349/d9rg87&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
visibility 20visibility views 20 download downloads 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25349/d9rg87&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2011Publisher:Environmental System Science Data Infrastructure for a Virtual Ecosystem; Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) Authors: Boden, Thomas; Marland, G.; Andres, Robert;Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2010), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, "in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources." Data from the U.S. Department of Interior's Geological Survey (USGS 2010) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999).
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3334/cdiac/00001_v2011&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu31 citations 31 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Article , Journal 2020Publisher:Elsevier BV Hee Chul Woo; Hoang Vu Ly; Hoang Vu Ly; Seung-Soo Kim; Jeong Woo Park; Jinsoo Kim; Hyun Tae Hwang;Abstract Bamboo has been considered a potential feedstock of energy for the future. It can be subjected to the pyrolysis for biofuels production. The thermogravimetric analysis (TGA) combined with differential thermogravimetric analysis (DTG) for bamboo was carried out prior to pyrolysis. The thermal degradation of bamboo was mainly between 230 and 420 °C. The conventional pyrolysis of bamboo was investigated in a bubbling fluidized-bed reactor using silica sand. The product distribution and composition of pyrolysis bio-oil were dependent on biomass component and operating conditions such as pyrolysis temperature, fluidization velocity, and particle size of biomass. The fractional catalytic pyrolysis of bamboo was also studied to upgrade the pyrolysis vapor, using HZSM-5 and red mud. The highest yield of bio-oil was 54.03 wt% compared to 49.14 wt% and 50.34 wt% of HZSM-5 and red mud catalyst, respectively. In the red mud catalytic pyrolysis, the oxygen content was rejected from pyrolysis vapor mostly via decarboxylation to produce more CO2 than CO; in contrast, for the HZSM-5 catalytic pyrolysis, the production of CO through decarbonylation was more favored than CO2. The main composition of catalytic pyrolysis bio-oil was 4-vinylphenol, which was employed as a raw material source to synthesize valuable material for energy storage.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2019.10.141&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 69 citations 69 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2019.10.141&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Report , Other literature type 2007 United StatesPublisher:Office of Scientific and Technical Information (OSTI) Authors: Agonafer, Dr. Dereje;doi: 10.2172/928422
The work described in this report was performed under the direction of the Industrial Assessment Center (IAC) at University of Texas at Arlington. The IAC at The University of Texas at Arlington is managed by Rutgers University under agreement with the United States Department of Energy Office of Industrial Technology, which financially supports the program. The objective of the IAC is to identify, evaluate, and recommend, through analysis of an industrial plant’s operations, opportunities to conserve energy and prevent pollution, thereby reducing the associated costs. IAC team members visit and survey the plant. Based upon observations made in the plant, preventive/corrective actions are recommended. At all times we try to offer specific and quantitative recommendations of cost savings, energy conservation, and pollution prevention to the plants we serve.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2172/928422&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.2172/928422&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2022Publisher:MDPI AG Ahmad Soltanzadeh; Mohsen Mahdinia; Alireza Omidi Oskouei; Ehsan Jafarinia; Esmaeil Zarei; Mohsen Sadeghi-Yarandi;doi: 10.3390/su142416555
Due to their unique nature, construction projects are considered one of the world’s most hazardous and incident-prone industrial sectors. The present study aimed to analyze health, safety and environmental (HSE) risks relating to construction projects based on the project management body of knowledge (PMBOK) and sustainability approach. This study was conducted with the participation of 30 experts, using the semi-quantitative risk assessment technique, in nine areas of the project management’s body of knowledge, based on the fuzzy analytic hierarchy process. Risk, in this study, was estimated using a two-dimensional matrix of incident probability and severity, each of which has four sub-parameters. The HSE risks pertaining to each of the nine areas of PMBOK were identified. After that, the two dimensions of risk, including incident probability and severity, were measured. Thirty-seven risk sources associated with nine areas of the PMBOK were identified. Risk analysis revealed that 20 sources were at an unacceptable risk level, and 17 risks were at a tolerable risk level. Identifying HSE-related risk sources in accordance with the nine areas of PMBOK, and using FAHP to assess the risk of these hazards in construction projects, can lead to a more realistic estimate of risk in construction projects. The presented method in the current study can create a novel perspective in terms of the construction industry’s risk management and assessment.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su142416555&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 10 citations 10 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/su142416555&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euapps Other research productkeyboard_double_arrow_right Other ORP type 2021 United StatesPublisher:World Bank, Washington, DC Authors: World Bank Group;handle: 10986/34971
The country’s unique philosophy is expressed by Bhutan’s Gross National Happiness (GNH) as the guiding principle of development. Bhutan is at a crossroads: It can maintain the current pattern of development—with rising inequality—or develop a vibrant private sector to generate jobs and diversify the economy, building resilience to future external shocks. The overarching priority of this Country Partnership Framework (CPF) is job creation. This CPF presents an integrated framework of WBG support to help Bhutan achieve inclusive and sustainable development through private sector–led job creation.
Open Knowledge Repos... arrow_drop_down Open Knowledge RepositoryOther ORP type . 2021License: CC BYData sources: Open Knowledge Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10986/34971&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert Open Knowledge Repos... arrow_drop_down Open Knowledge RepositoryOther ORP type . 2021License: CC BYData sources: Open Knowledge Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10986/34971&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2019Publisher:Wiley Lídia Cantacorps; Lídia Cantacorps; Rainer Spanagel; Olga Valverde; Shoupeng Wei; Ainhoa Bilbao; Sarah Leixner;doi: 10.1111/adb.12784
pmid: 31237390
AbstractThe co‐occurrence of chronic pain and alcohol use disorders (AUDs) involves complex interactions between genetic and neurophysiological aspects, and the research has reported mixed findings when they both co‐occur. There is also an indication of a gender‐dependent effect; males are more likely to use alcohol to cope with chronic pain problems than females. Recently, a new conceptualization has emerged, proposing that the negative affective component of pain drives and maintains alcohol‐related behaviors. We studied in a longitudinal fashion alterations in alcohol drinking patterns and pain thresholds in a mouse model of chronic neuropathic pain in a sex‐dependent manner. Following partial denervation (spared nerve injury [SNI]), stimulus‐evoked pain responses were measured before chronic alcohol consumption, during drinking, during a deprivation phase, and following an episode of excessive drinking. During the course of alcohol drinking, we observed pronounced sex differences in pain thresholds. Male mice showed a strong increase in pain thresholds, suggesting an analgesic effect induced by alcohol over time, an effect that was not observed in female mice. SNI mice did not differ from sham‐operated controls in baseline alcohol consumption. However, following a deprivation phase and the reintroduction of ethanol, male SNI mice but not female mice showed more pronounced excessive drinking than controls. Finally, we observed decreased central ethanol sensitivity in male SNI mice but not in females. Together with our finding, that ethanol is able to decrease a pain‐induced negative affective memory we come to following conclusion. We propose that a lower sensitivity to the intoxicating effects of alcohol together with the ability of alcohol to reduce the negative affective component of pain may explain the higher co‐occurrence of AUD in male chronic pain patients.
Addiction Biology arrow_drop_down Addiction BiologyArticle . 2019 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/adb.12784&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesbronze 13 citations 13 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Addiction Biology arrow_drop_down Addiction BiologyArticle . 2019 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/adb.12784&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:NSF Arctic Data Center Atwood, Trisha; Beard, Karen; Waring, Bonnie; Adkins, Jaron; Saunders, Taylor;doi: 10.18739/a2cc0tv7w
Global change drivers that modify the quality and quantity of litter inputs to soil affect greenhouse gas fluxes, and thereby constitute a feedback to climate change. Carbon cycling in the Yukon-Kuskokwim (Y-K) River Delta, a subarctic wetland system, is influenced by landscape variations in litter quality and quantity generated by herbivores (migratory birds) that create ‘grazing lawns’ of short stature, nitrogen-rich vegetation. To identify the mechanisms by which these changes in litter inputs affect soil carbon balance, we independently manipulated qualities and quantities of litter representative of levels found in the Y-K Delta in a fully factorial microcosm experiment. We measured carbon dioxide (CO2) fluxes from these microcosms weekly. To help us identify how litter inputs influenced greenhouse gas fluxes, we sequenced soil fungal and bacterial communities, and measured soil microbial biomass carbon, dissolved carbon, inorganic nitrogen, and enzyme activity. We found that positive correlations between litter input quantity and CO2 flux were dependent upon litter type, due to differences in litter stoichiometry and changes to the structure of decomposer communities, especially the soil fungi. These community shifts were particularly pronounced when litter was added in the form of herbivore feces, and in litter input treatments that induced nitrogen limitation (i.e., senesced litter). The sensitivity of carbon cycling to litter quality and quantity in this system demonstrates that herbivores can strongly impact greenhouse gas fluxes through their influence on plant growth and tissue chemistry.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18739/a2cc0tv7w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18739/a2cc0tv7w&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 12 Jan 2023Publisher:Dryad Floess, Emily; Grieshop, Andrew; Puzzolo, Elisa; Pope, Daniel; Leach, Nicholas; Smith, Christopher J.; Gill-Wiehl, Annelise; Landesman, Katherine; Bailis, Robert;Nearly three billion people in low- and middle-income countries (LMICs) rely on polluting fuels, resulting in millions of avoidable deaths annually. Polluting fuels also emit short-lived climate forcers and greenhouse gases (GHGs). Liquefied petroleum gas (LPG) and grid-based electricity are scalable alternatives to polluting fuels but have raised climate and health concerns. Here, we compare emissions and climate impacts of a business-as-usual household cooking fuel trajectory to four large-scale transitions to gas and/or grid electricity in 77 LMICs. We account for upstream and end-use emissions from gas and electric cooking, assuming electrical grids evolve according to the 2022 World Energy Outlook’s “Stated Policies” Scenario. We input the emissions into a reduced-complexity climate model to estimate radiative forcing and temperature changes associated with each scenario. We find full transitions to LPG and/or electricity decrease emissions from both well-mixed GHG and short-lived climate forcers, resulting in a roughly 5 millikelvin global temperature reduction by 2040. Transitions to LPG and/or electricity also reduce annual emissions of PM2.5 by over 6 Mt (99%) by 2040, which would substantially lower health risks from Household Air Pollution. Primary input data was collected from the following sources: Baseline household fuel choices - WHO household energy database (https://www.nature.com/articles/s41467-021-26036-x) End-use emissions - US EPA lifecycle assessment of household fuels (https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=339679&Lab=NRMRL&simplesearch=0&showcriteria=2&sortby=pubDate&timstype=Published+Report&datebeginpublishedpresented) Upstream emissions - Argonne National Labs GREET Model (https://greet.es.anl.gov/index.php) Current and future population estimates - UNECA (http://data.un.org/Explorer.aspx?d=EDATA) Input data was processed by defining household fuel choice scenarios, estimating national household fuel consumption based on these scenarios, and applying fuel-specific emission factors to create country-specific emission pathways. These emission pathways were input into the FaIR model (https://zenodo.org/record/5513022#.Yt_jfHbMLb0) which generated additional data for each scenario including time series of pollution concentrations, radiative forcing, and temperature changes. All data is provided in CSV format. Nothing proprietary is required.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5061/dryad.jq2bvq8d9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Top 10% influence Average impulse Average Powered by BIP!
visibility 3visibility views 3 download downloads 2 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5061/dryad.jq2bvq8d9&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Embargo end date: 30 Jul 2019Publisher:Harvard Dataverse Authors: Scarpelli, Tia R.; Jacob, Daniel J.;doi: 10.7910/dvn/hh4eum
This is the Global Fuel Exploitation Inventory (GFEI) which provides a 0.1 x 0.1 degree grid of methane emissions of fugitive emissions related to oil, gas, and coal activities (IPCC Sector 1B1 and 1B2). Subsector emissions are provided from exploration to distribution of the resource. The inventory emissions are based on individual country reports submitted in accordance with the United Nations Framework Convention on Climate Change (UNFCCC). For those countries that do not report we estimate emissions following IPCC methods. Emissions are allocated to infrastructure locations including mines, wells, pipelines, compressor stations, storage facilities, processing plants, and refineries. This version of the inventory (GFEI v3) inventory is for 2020 and presents an update of GFEI v2 and v1 which were for 2019 and 2016, respectively. Emission grids are also available for 2010-2019. In GFEI v3, for each sector (oil, gas, coal) and subsector (exploration, production, etc.) there are emission grids. File names are in netcdf format and should start with "Global_Fuel_Exploitation_Inventory_v3_2020_" followed by the sector or subsector name. Please contact us if you would like emissions for an alternate year. We will also make input data and code available upon reasonable request.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.7910/dvn/hh4eum&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.7910/dvn/hh4eum&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Embargo end date: 08 Jun 2022Publisher:Dryad Brady, Hannah; Barsotti, Gabrielle; Davis, Jordan; Norris, Carly; Shaphran, Eric;doi: 10.25349/d9rg87
In recent years, there has been increased attention and focus from the public on the environmental impact of professional sports organizations. Significant opportunities exist for Major League Baseball (MLB) teams to both reduce their own environmental footprint, and that of their fans, through sustainability initiatives. Despite stadiums using upwards of ten million gallons of water per year and having the same energy needs as a small city, no MLB team has completed a public-facing quantification of their total environmental footprint. This project calculated the carbon footprint and water consumption of the Tampa Bay Rays for the 2019 regular season. We analyzed Scope 1, 2, and 3 GHG emissions to identify hotspots within the Rays’ operations, supply chains, and transportation. Fan transportation was found to be the largest source of GHGs, followed by food production for concessions. The cooling tower and restrooms were identified as the largest sources of onsite water usage. We created a repository of best practices as a resource for stadium managers that includes strategies to reduce GHGs and water use coupled with scenario analyses estimating potential reductions. The following recommendations are highlighted as the largest reduction opportunities: (1) prioritizing fan engagement to switch to more sustainable modes of transportation, and (2) offering and highlighting more vegetarian options at concessions. To further reduce emissions and water usage, MLB teams should prioritize sub-metering electricity and water lines and installing more efficient equipment. Data was provided by the Tampa Bay Rays and collected at Tropicana Field (where the Rays play) by Jordan Davis during the summer of 2021.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25349/d9rg87&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
visibility 20visibility views 20 download downloads 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.25349/d9rg87&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2011Publisher:Environmental System Science Data Infrastructure for a Virtual Ecosystem; Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) Authors: Boden, Thomas; Marland, G.; Andres, Robert;Publications containing historical energy statistics make it possible to estimate fossil fuel CO2 emissions back to 1751. Etemad et al. (1991) published a summary compilation that tabulates coal, brown coal, peat, and crude oil production by nation and year. Footnotes in the Etemad et al.(1991) publication extend the energy statistics time series back to 1751. Summary compilations of fossil fuel trade were published by Mitchell (1983, 1992, 1993, 1995). Mitchell's work tabulates solid and liquid fuel imports and exports by nation and year. These pre-1950 production and trade data were digitized and CO2 emission calculations were made following the procedures discussed in Marland and Rotty (1984) and Boden et al. (1995). Further details on the contents and processing of the historical energy statistics are provided in Andres et al. (1999). The 1950 to present CO2 emission estimates are derived primarily from energy statistics published by the United Nations (2010), using the methods of Marland and Rotty (1984). The energy statistics were compiled primarily from annual questionnaires distributed by the U.N. Statistical Office and supplemented by official national statistical publications. As stated in the introduction of the Statistical Yearbook, "in a few cases, official sources are supplemented by other sources and estimates, where these have been subjected to professional scrutiny and debate and are consistent with other independent sources." Data from the U.S. Department of Interior's Geological Survey (USGS 2010) were used to estimate CO2 emitted during cement production. Values for emissions from gas flaring were derived primarily from U.N. data but were supplemented with data from the U.S. Department of Energy's Energy Information Administration (1994), Rotty (1974), and data provided by G. Marland. Greater details about these methods are provided in Marland and Rotty (1984), Boden et al. (1995), and Andres et al. (1999).
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3334/cdiac/00001_v2011&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu31 citations 31 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
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