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description Publicationkeyboard_double_arrow_right Article , Other literature type 2025Embargo end date: 06 Jan 2025 United KingdomPublisher:Springer Science and Business Media LLC Funded by:NSF | Tracing Past Methane Vari...NSF| Tracing Past Methane Variations with Stable Isotopes in Antarctic Ice CoresAuthors:Ben Riddell-Young;
Ben Riddell-Young
Ben Riddell-Young in OpenAIREJames Edward Lee;
James Edward Lee
James Edward Lee in OpenAIREEdward J. Brook;
Edward J. Brook
Edward J. Brook in OpenAIREJochen Schmitt;
+5 AuthorsJochen Schmitt
Jochen Schmitt in OpenAIREBen Riddell-Young;
Ben Riddell-Young
Ben Riddell-Young in OpenAIREJames Edward Lee;
James Edward Lee
James Edward Lee in OpenAIREEdward J. Brook;
Edward J. Brook
Edward J. Brook in OpenAIREJochen Schmitt;
Jochen Schmitt
Jochen Schmitt in OpenAIREHubertus Fischer;
Hubertus Fischer
Hubertus Fischer in OpenAIREThomas K. Bauska;
Thomas K. Bauska
Thomas K. Bauska in OpenAIREJames A. Menking;
James A. Menking
James A. Menking in OpenAIRERené Iseli;
René Iseli
René Iseli in OpenAIREJustin Reid Clark;
Justin Reid Clark
Justin Reid Clark in OpenAIREpmid: 39743610
Understanding the causes of past atmospheric methane (CH4) variability is important for characterizing the relationship between CH4, global climate and terrestrial biogeochemical cycling. Ice core records of atmospheric CH4 contain rapid variations linked to abrupt climate changes of the last glacial period known as Dansgaard-Oeschger (DO) events and Heinrich events (HE)1,2. The drivers of these CH4 variations remain unknown but can be constrained with ice core measurements of the stable isotopic composition of atmospheric CH4, which is sensitive to the strength of different isotopically distinguishable emission categories (microbial, pyrogenic and geologic)3-5. Here we present multi-decadal-scale measurements of δ13C-CH4 and δD-CH4 from the WAIS Divide and Talos Dome ice cores and identify abrupt 1‰ enrichments in δ13C-CH4 synchronous with HE CH4 pulses and 0.5‰ δ13C-CH4 enrichments synchronous with DO CH4 increases. δD-CH4 varied little across the abrupt CH4 changes. Using box models to interpret these isotopic shifts6 and assuming a constant δ13C-CH4 of microbial emissions, we propose that abrupt shifts in tropical rainfall associated with HEs and DO events enhanced 13C-enriched pyrogenic CH4 emissions, and by extension global wildfire extent, by 90-150%. Carbon cycle box modelling experiments7 suggest that the resulting released terrestrial carbon could have caused from one-third to all of the abrupt CO2 increases associated with HEs. These findings suggest that fire regimes and the terrestrial carbon cycle varied contemporaneously and substantially with past abrupt climate changes of the last glacial period.
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For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Top 10% 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.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2025 DenmarkPublisher:Institute of Electrical and Electronics Engineers (IEEE) Authors: Jiaxiang Hu;Weihao Hu;
Weihao Hu
Weihao Hu in OpenAIREDi Cao;
Di Cao
Di Cao in OpenAIREQianwen Xu;
+3 AuthorsQianwen Xu
Qianwen Xu in OpenAIREJiaxiang Hu;Weihao Hu;
Weihao Hu
Weihao Hu in OpenAIREDi Cao;
Di Cao
Di Cao in OpenAIREQianwen Xu;
Qianwen Xu
Qianwen Xu in OpenAIREQi Huang;
Qi Huang
Qi Huang in OpenAIREZhe Chen;
Zhe Chen
Zhe Chen in OpenAIREFrede Blaabjerg;
Frede Blaabjerg
Frede Blaabjerg in OpenAIREThe training process of learning-based distribution system state estimation (DSSE) methods relies on accurate state variables, which typically contain unknown noise and outliers in practice. To this end, this paper proposes an adaptive noise-resistant graphical learning-based DSSE method considering the impact of inaccurate state variables. Specifically, two global-scanning graph jumping connection networks are first developed to capture the regression rules between measurements and state variables considering the structure constraints. To mitigate the negative impact caused by inaccurate labels, a collaborative learning framework is further developed, within which Gaussian mixture model-based discriminators are employed to adaptively select clean samples in each mini-batch. These allow the method to obtain robustness against noisy state labels in historical data, as well as anomalous measurements during online operations. Comparative tests show the superiority of the proposed method in tackling abnormal data in both the training and test phases.
Aalborg University R... arrow_drop_down IEEE Transactions on Power SystemsArticle . 2025 . Peer-reviewedLicense: IEEE CopyrightData 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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more_vert Aalborg University R... arrow_drop_down IEEE Transactions on Power SystemsArticle . 2025 . Peer-reviewedLicense: IEEE CopyrightData 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.eudescription Publicationkeyboard_double_arrow_right Article 2025 DenmarkPublisher:Institute of Electrical and Electronics Engineers (IEEE) Authors:Chang Yang;
Chang Yang
Chang Yang in OpenAIRETao Zheng;
Yufei Song;Tao Zheng
Tao Zheng in OpenAIREJiefeng Hu;
+1 AuthorsJiefeng Hu
Jiefeng Hu in OpenAIREChang Yang;
Chang Yang
Chang Yang in OpenAIRETao Zheng;
Yufei Song;Tao Zheng
Tao Zheng in OpenAIREJiefeng Hu;
Jiefeng Hu
Jiefeng Hu in OpenAIREJosep M. Guerrero;
Josep M. Guerrero
Josep M. Guerrero in OpenAIREIn a hybrid AC/DC microgrid (MG), power quality issues arise when an unbalanced load connects to the AC subgrid, which are not confined to the AC subsystem but extend to affect the DC subsystem as well. This paper investigates the potential power quality issues caused by AC imbalance, including DC voltage fluctuation and AC current harmonics. Multiple control objectives are developed, aiming to eliminate DC fluctuation, reduce AC distortion and imbalance, and achieve negative sequence current sharing among distributed generations in the AC subgrid. To realize these control objectives, a two-layer coordinated control strategy is proposed. The first layer involves local interlinking converter (IC) control to improve the power quality of the DC subgrid, while the second layer focuses on distributed unbalance compensation control to improve the power quality of the AC subgrid. Finally, several experiments are conducted to verify the effectiveness of the proposed control strategy.
Aalborg University R... arrow_drop_down IEEE Transactions on Smart GridArticle . 2025 . Peer-reviewedLicense: IEEE CopyrightData 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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more_vert Aalborg University R... arrow_drop_down IEEE Transactions on Smart GridArticle . 2025 . Peer-reviewedLicense: IEEE CopyrightData 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=10.1109/tsg.2024.3458388&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2025Embargo end date: 05 Mar 2025 CanadaPublisher:Borealis Authors: International Energy Agency;doi: 10.5683/sp3/0ignzm
This file shows the net electricity and heat production by autoproducers in all plants, in 40 sectors. It contains 38 OECD countries, 14 non-OECD countries, and 7 aggregates. Data are in GWh and TJ, and begin in 1974. [Dataset editions 2015-2016, 2018-2023]. IEA Electricity Information Statistics
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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.euResearch data keyboard_double_arrow_right Dataset 2025Embargo end date: 05 Mar 2025 CanadaPublisher:Borealis Authors: International Energy Agency;doi: 10.5683/sp3/lr02yc
2015-2023 editions of the data. Mexico data is included in the 2019-2022 editions. Lithuania data is included in the 2020-2022 editions. The 2023 edition of the data contains less countries than in any other version; countries included are Australia, Austria, Belgium, Canada, Colombia, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy. This table includes statistical projections on the energy balance for IEA countries by analyzing their respective products (coal, oil, nuclear, hydro, biofuels and more) in terms of flow. Data are expressed in thousand tonnes of oil equivalent(ktoe) and forecasts extend to 2030. [Data editions 2015-2023] Energy Projections for IEA Countries
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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=10.5683/sp3/lr02yc&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2025Embargo end date: 05 Mar 2025 CanadaPublisher:Borealis Authors: International Energy Agency;doi: 10.5683/sp3/d1ooqy
<p>In this table, a balance for different types of coal and coal products, including manufactured gases is shown. The aggregates for hard coal and brown coal are also included, as is a product coal which includes all primary coal types, and all derived coal products with the exception of gas works gas. This table provides full balance data such as primary energy supply, transformation sector and final consumption based in kilotonnes of coal equivalent (7,000 Gigacalories) for OECD countries and OECD country aggregate groups. </p> <p> This table provides full energy balance data of coal and other products such as primary energy supply, transformation sector and final consumption. Products: anthracite, coking coal, other bituminous coal, sub-bituminous coal, lignite, patent fuel, coke oven coke, gas coke, coal tar, BKB, gas works gas, coke oven gas, blast furnace gas, other recovered gases, peat, peat products and oil shale and oil sands. The aggregates hard coal, brown coal and steam coal are also included. Units: kilotons of coal equivalent (7,000 Gigacalories), kilotons of oil equivalent (10,000 Gigacalories), Terajoules and Teracalories. Electricity and Heat output flows are in Gigawatt-hour and Terajoules, respectively. [Data editions 2015-2023]</p> IEA Coal Information Statistics
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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=10.5683/sp3/d1ooqy&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2025Embargo end date: 05 Mar 2025 CanadaPublisher:Borealis Authors: International Energy Agency;doi: 10.5683/sp3/l0nsto
This dataset comprises statistics regarding various renewable and waste energy while presenting trade statistics of various renewable energy products as well as figures for those products in terms of electricity output (GWh) and heat output(TJ). [Dataset editions 2015-2023]. IEA Renewables Information Statistics
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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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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.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2025Embargo end date: 05 Mar 2025 CanadaPublisher:Borealis Authors: International Energy Agency;doi: 10.5683/sp3/txppjz
This comparative table comprises statistics about net capacity of renewables in MWe terms. Renewable electricity and heat generation are derived from solar thermal, geothermal, hydro, wind. [Dataset editions 2015-2023]. IEA Renewables Information Statistics
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2025Embargo end date: 05 Mar 2025 CanadaPublisher:Borealis Authors: International Energy Agency;doi: 10.5683/sp3/ih8ahq
This dataset includes data on Industry energy use, Industry activity, Industry emissions as well as Industry energy and carbon indicators. [Dataset editions 2021-2023]. IEA Energy Efficiency Indicators
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2025Embargo end date: 05 Mar 2025 CanadaPublisher:Borealis Authors: International Energy Agency;doi: 10.5683/sp3/zcurad
This dataset focuses on the renewables market while providing full balance data such as primary energy supply, transformation sector and final consumption based in kilotonne and terajoule of renewables equivalent for OECD countries and OECD country aggregate. [Dataset editions 2015-2023]. IEA Renewables Information Statistics
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