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description Publicationkeyboard_double_arrow_right Article , Other literature type 2019Publisher:Springer Science and Business Media LLC Mukhtar Ahmed; Claudio O. Stöckle; Roger Nelson; Stewart S. Higgins; Shakeel Ahmad; Muhammad Ali Raza;pmid: 31127159
pmc: PMC6534615
AbstractElevated carbon-dioxide concentration [eCO2] is a key climate change factor affecting plant growth and yield. Conventionally, crop modeling work has evaluated the effect of climatic parameters on crop growth, without considering CO2. It is conjectured that a novel multimodal ensemble approach may improve the accuracy of modelled responses to eCO2. To demonstrate the applicability of a multimodel ensemble of crop models to simulation of eCO2, APSIM, CropSyst, DSSAT, EPIC and STICS were calibrated to observed data for crop phenology, biomass and yield. Significant variability in simulated biomass production was shown among the models particularly at dryland sites (44%) compared to the irrigated site (22%). Increased yield was observed for all models with the highest average yield at dryland site by EPIC (49%) and lowest under irrigated conditions (17%) by APSIM and CropSyst. For the ensemble, maximum yield was 45% for the dryland site and a minimum 22% at the irrigated site. We concluded from our study that process-based crop models have variability in the simulation of crop response to [eCO2] with greater difference under water-stressed conditions. We recommend the use of ensembles to improve accuracy in modeled responses to [eCO2].
https://doi.org/10.1... arrow_drop_down https://doi.org/10.1038/s41598...Article . 2019 . Peer-reviewedLicense: CC BYData 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.Access RoutesGreen gold 51 citations 51 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert https://doi.org/10.1... arrow_drop_down https://doi.org/10.1038/s41598...Article . 2019 . Peer-reviewedLicense: CC BYData 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.description Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type 2017Publisher:Springer Science and Business Media LLC Funded by:ANR | VIRGOANR| VIRGOAuthors: Mathias, Jean-Denis; Anderies, J.M.; Janssen, M.A.;AbstractThe planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO2 concentration of 550 ppm until 2100 and (2) returning to 350 ppm in 2100. Our results enable decision makers to assess the following milestones: (1) a minimum of 33% reduction of CO2 emissions by 2055 in order to stay below 550 ppm by 2100 (this milestone goes up to 46% in the case of delayed policies); and (2) carbon neutrality and the effective implementation of innovative geoengineering technologies (10% negative emissions) before 2060 in order to return to 350 ppm in 2100, under the assumption of getting out of the baseline scenario without delay. Finally, we emphasize the need to use adaptive path-based approach instead of single point target for climate policy design.
Arizona State Univer... arrow_drop_down Arizona State University: ASU Digital RepositoryArticle . 2017License: CC BYFull-Text: http://hdl.handle.net/2286/R.I.44365Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.1038/srep42...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefInstitut National de la Recherche Agronomique: ProdINRAArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)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.Access RoutesGreen gold 24 citations 24 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Arizona State Univer... arrow_drop_down Arizona State University: ASU Digital RepositoryArticle . 2017License: CC BYFull-Text: http://hdl.handle.net/2286/R.I.44365Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.1038/srep42...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefInstitut National de la Recherche Agronomique: ProdINRAArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)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.description Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type 2020Publisher:Copernicus GmbH Giorgia Bagagiolo; Danilo Rabino; Marcella Biddoccu; Guido Nigrelli; Daniele Cat Berro; Luca Mercalli; Federico Spanna; Giorgio Capello; Eugenio Cavallo;<p>Historical weather data represent an extremely precious resource for agro-meteorology for studying evolutionary dynamics and for predictive purposes, to address agronomical and management choices, that have economic, social and environmental effect. The study of climatic variability and its consequences starts from the observation of variations over time and the identification of the causes, on the basis of historical series of meteorological observations. The availability of long-lasting, complete and accurate datasets is a fundamental requirement to predict and react to climate variability. Inter-annual climate changes deeply affect grapevine productive cycle determining direct impact on the onset and duration of phenological stages and, ultimately, on the grape harvest and yield. Indeed, climate variables, such as air temperature and precipitation, affect evapotranspiration rates, plant water requirements, and also the vine physiology. In this respect, the observed increase in the number of warm days poses a threat to grape quality as it creates a situation of imbalance at maturity, with respect to sugar content, acidity and phenolic and aromatic ripeness.</p><p>A study was conducted to investigate the relationships between climate variables and harvest onset dates to assess the responses of grapevine under a global warming scenario. The study was carried out in the &#8220;Monferrato&#8221; area, a rainfed hillslope vine-growing area of NW Italy. In particular, the onset dates of harvest of different local wine grape varieties grown in the Vezzolano Experimental Farm (CNR-IMAMOTER) and in surrounding vineyards (affiliated to the Terre dei Santi Cellars) were recorded from 1962 to 2019 and then related to historical series of climate data by means of regression analysis. The linear regression was performed based on the averages of maximum and minimum daily temperatures and sum of precipitation (1962&#8211;2019) calculated for growing and ripening season, together with a bioclimatic heat index for vineyards, the Huglin index. The climate data were obtained from two data series collected in the Experimental farm by a mechanical weather station (1962-2002) and a second series recorded (2002-2019) by an electro-mechanical station included in Piedmont Regional Agro-meteorological Network. Finally, a third long-term continuous series covering the period from 1962 to 2019, provided by Italian Meteorological Society was considered in the analysis.</p><p>The results of the study highlighted that inter-annual climate variability, with a general positive trend of temperature, significantly affects the ripening of grapes with a progressive anticipation of the harvest onset dates. In particular, all the considered variables excepted precipitation, resulted negatively correlated with the harvest onset date reaching a high level of significance (up to P< 0.001). Best results have been obtained for maximum temperature and Huglin index, especially by using the most complete dataset. The change ratios obtained using datasets including last 15 years were greater (in absolute terms) than results limited to the period 1962-2002, and also correlations have greater level of significance. The results indicated clearly the relationships between the temperature trend and the gradual anticipation of harvest and the importance of having long and continuous historical weather data series available.</p>
IRIS Cnr arrow_drop_down Publications Open Repository TOrinoArticle . 2021License: CC BY NC NDData sources: Publications Open Repository TOrinoItalian Journal of AgrometeorologyArticle . 2021 . Peer-reviewedLicense: CC BYData 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.Access RoutesGreen gold 6 citations 6 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert IRIS Cnr arrow_drop_down Publications Open Repository TOrinoArticle . 2021License: CC BY NC NDData sources: Publications Open Repository TOrinoItalian Journal of AgrometeorologyArticle . 2021 . Peer-reviewedLicense: CC BYData 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.description Publicationkeyboard_double_arrow_right Article 2022Publisher:MDPI AG Authors: Leijiao Ge; Jun Yan; Yonghui Sun; Zhongguan Wang;doi: 10.3390/en15114164
In recent years, the accelerating climate change and intensifying natural disasters have called for more renewable, resilient, and reliable energy from more distributed sources to more diversified consumers, resulting in a pressing need for advanced situational awareness of modern smart distribution systems [...]
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.Access Routesgold 2 citations 2 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.description Publicationkeyboard_double_arrow_right Article , Other literature type 2017Publisher:MDPI AG Baohua Xie; Jiangxin Gu; Junbao Yu; Guangxuan Han; Xunhua Zheng; Yu Xu; Haitao Lin;doi: 10.3390/atmos8100181
Land use changes from cropland to orchards in Eastern China have raised serious concerns about the regional nitrogen (N) cycle and greenhouse gas balance. We measured soil nitrous oxide (N2O) emissions and methane (CH4) uptake using manual static chambers in an apple orchard. The primary aims were to assess the effect of N fertilizer application on gas fluxes and quantify the site-specific N2O emission factor (EFd). Field experiments were arranged in a randomized block design with three N input rates (0, 800 and 2600/2000 kg N ha−1 year−1). We found that orchard soils were a negligible CH4 sink (−1.1 to −0.4 kg C ha−1 year−1). Annual N2O emissions responded positively to N input rates, ranging from 34.1 to 60.3 kg N ha−1 year−1. EFd ranged from 1.00% to 1.65% with a mean of 1.34%. The extremely large background emissions of N2O (34.1–34.3 kg N ha−1 year−1) most likely originated from nitrate accumulation in the soil profile because of historical overuse of N fertilizer. We conclude that (1) site-specific EFd is suitable for assessing regional direct N2O emissions from upland orchards; and (2) conventional fertilization regimes must be avoided, and reduced N input rates are recommended in the study region.
Atmosphere arrow_drop_down AtmosphereOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2073-4433/8/10/181/pdfData sources: Multidisciplinary Digital Publishing Instituteadd 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.Access Routesgold 23 citations 23 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert Atmosphere arrow_drop_down AtmosphereOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2073-4433/8/10/181/pdfData sources: Multidisciplinary Digital Publishing Instituteadd 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.description Publicationkeyboard_double_arrow_right Article 2023Publisher:Frontiers Media SA Funded by:EC | IntelCompEC| IntelCompPapadaki, Lydia; Stavridis, Charalampos; Koundouri, Phoebe; Grypari, Ioanna; Kazbek, Madina; Papageorgiou, Haris; Theodossiou, Nicolaos;The phenomena of climate change transcend all national and regional boundaries. To address this complex challenge, we must determine the areas of the country of interest, in this case, Greece, that have been most adversely affected by climate. Greece is surrounded by water, and a significant part of its GDP is derived from the marine and maritime industries, including tourism. Since the start of the IntelComp project, a Preparatory Living Lab (PLL) has been planned and delivered, feeding into the development of the IntelComp platform and the Living Lab on Climate Change Adaptation. The study's results lead to the conclusion that one of the most important challenges in tackling climate change is the decarbonisation challenge, specifically the shift to renewable energy sources and the investments that must be made. Several EU and national policy frameworks, including the European Green Deal, the Climate Law, the National Long-term Strategy for 2050 (on the Climate and Energy), highlight the decarbonisation as one of the major challenges in the climate change pledge. This will be the primary subject of the IntelComp climate change case study. PLLs also led to the identification of policy questions and useful data sources to aid the IntelComp project's launch. While previous research on co-production has primarily focused on involving citizens through public participation processes in order to gain their support, trust, and insights in structured decision-making processes, our approach opens a new channel for incorporating external knowledge into problem-solving processes. The IntelComp project will aid in policy development by providing pertinent tools co-developed with the final users that will provide insights and analysis in the field of STI (Science, Technology, Innovation) encompassing all of the Energy areas mentioned above.
Frontiers in Environ... arrow_drop_down Frontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefOnline Research Database In TechnologyArticle . 2023Data sources: Online Research Database In TechnologyFrontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedData sources: European Union Open Data Portaladd 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.Access RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
more_vert Frontiers in Environ... arrow_drop_down Frontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefOnline Research Database In TechnologyArticle . 2023Data sources: Online Research Database In TechnologyFrontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedData sources: European Union Open Data Portaladd 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.description Publicationkeyboard_double_arrow_right Article 2016Publisher:Elsevier BV Zhao, Hong; Gao, Yang; Wang, Jian; Chen, Chi; Chen, Dengjie; Wang, Chen; Ciucci, Francesco;Abstract Egg yolk-derived P and N dual doped nano carbon capsules (PNCCs) have been synthesized and used as lithium ion battery anodes. The application of egg yolk as the carbon source is a new and environmental-friendly approach for biomass recycling. The reversible capacity of half cells made of PNCCs is as high as ~770 mA h g−1 at a current density of 0.5 A g−1 with considerable rate capacity and cycling stability. PNCCs show a capsule-like structure, which provide extra edges and active sites for lithium intercalation. The heteroatom doping also introduce defects and disorder, which increases the electrochemical activity and creates more active sites for lithium insertion.
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.40 citations 40 popularity Top 10% influence Top 10% 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.description Publicationkeyboard_double_arrow_right Article 2023Publisher:Elsevier BV Yong, Wang; Huachao, Xu; Ying, Li; Na, Lin; Peilong, Xu;pmid: 37586484
This study aims to introduce, conceptualize, and design a novel biomass/gasification-driven hybrid energy configuration. The proposed hybrid configuration has four subsystems: reformer solid oxide fuel cell (RSOFC), biomass/gasification, homogeneous charge compression ignition engine (HCCIE) plus waste heat recovery system (WHRS). RSOFC and HCCIE systems are embedded to generate electric energy. The syngas required for these two subsystems is captured from the biomass/gasification subsystem. In addition to generating electrical energy, fuel cell is responsible for providing combustible fuel to the HCCIE subsystem. The embedded engine in the system can improve the proposed configuration efficiency by increasing the rate of electrical energy production. In addition, the dissipated heat of fuel cell and engine subsystems is recovered by WHRS. The proposed energy configuration is evaluated and discussed from energetically, exergetically and exergoeconomic and environmental aspects to obtain a comprehensive feasibility study of the plant. The offered hybrid design has new component's structure and relationships that have not been reported in the publications. The analysis indicated that the proposed hybrid configuration is capable of generating approximately 1100 kW and 366.3 W of electric and thermal power, respectively, with the overall energetic and exergetic efficiencies of 69.4% and 52.1%. Exergoeconomic analysis results revealed that the specific fuel cost of the total proposed configuration was approximately 1.96 USD per GJ. In addition, compared to a coal and petroleum oil-based power generation plants, the proposed hybrid configuration can have approximately 2.75-fold and 97.7% lower CO2 emissions, sequentially. Besides, the proposed system can rival other similar biomass-driven designs.
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.7 citations 7 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.description Publicationkeyboard_double_arrow_right Article 2023Publisher:Elsevier BV Mazzeo D.; Leva S.; Matera N.; Kontoleon K. J.; Saboor S.; Pirouz B.; Elkadeem M. R.;handle: 20.500.11770/358598 , 11311/1243737
While traditional methods for modelling the thermal and electrical behaviour of photovoltaic (PV) modules rely on analytical and empirical techniques, machine learning is gaining interest as a way to reduce the time, expertise, and tools required by designers or experts while maintaining high accuracy and reliability. This research presents a data-driven machine learning tool based on artificial neural networks (ANNs) that can forecast yearly PV electricity directly at the optimal PV inclination angle without geographic restrictions and is valid for a wide range of electrical characteristics of PV modules. Additionally, empirical correlations were developed to easily determine the optimal PV inclination angle worldwide. The ANN algorithm, developed in Matlab, systematically and quantitatively summarizes the behaviour of eight PV modules in 48 worldwide climatic conditions. The algorithm’s applicability and robustness were proven by considering two different PV modules in the same 48 locations. Yearly climatic variables and electrical/thermal PV module parameters serve as input training data. The yearly PV electricity is derived using dynamic simulations in the TRNSYS environment, which is a simulation program primarily and extensively used in the fields of renewable energy engineering and building simulation for passive as well as active solar design. Multiple performance metrics validate that the ANN-based machine learning tool demonstrates high reliability and accuracy in the PV energy production forecasting for all weather conditions and PV module characteristics. In particular, by using 20 neurons, the highest value of R-square of 0.9797 and the lowest values of the root mean square error and coefficient of variance of 14.67 kWh and 3.8%, respectively, were obtained in the training phase. This high accuracy was confirmed in the ANN validation phase considering other PV modules. An R-square of 0.9218 and values of the root mean square error and coefficient of variance of 31.95 kWh and 7.8%, respectively, were obtained.The results demonstrate the algorithm’s vast potential to enhance the worldwide diffusion and economic growth of solar energy, aligned with the seventh sustainable development goal.
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.Access RoutesGreen gold 14 citations 14 popularity Top 10% influence Top 10% 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.description Publicationkeyboard_double_arrow_right Article 2019Publisher:Elsevier BV Authors: Lehtola, Timo; Zahedi, Ahmad;Abstract Solar energy and wind power supply are renewable, decentralised and intermittent electrical power supply methods that require energy storage. Integrating this renewable energy supply to the electrical power grid may reduce the demand for centralised production, making renewable energy systems more easily available to remote regions. Control systems optimise solar energy and wind power sources to supply renewable energy to the power grid. Vehicle to Grid (V2G) operations support intermittent production as battery storage. In V2G operations, electric power flows from the power grid to the battery storage and from the battery storage back to the power grid. The primary goal of this study is to improve the existing renewable energy supply to provide more reliable units in the power grid. We consider the V2G concept as an extension of the smart charging system allowing electric vehicles to be able to inject battery energy into the power grid, acting as distributed generators or energy storage systems. This review shows how parallel V2G storage and battery storage supports the power grid. Further, the review indicates that decentralised V2G battery storages will be included in future renewable energy systems.
Sustainable Energy T... arrow_drop_down Sustainable Energy Technologies and AssessmentsArticle . 2019 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefJames Cook University, Australia: ResearchOnline@JCUArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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.138 citations 138 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Sustainable Energy T... arrow_drop_down Sustainable Energy Technologies and AssessmentsArticle . 2019 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefJames Cook University, Australia: ResearchOnline@JCUArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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.
description Publicationkeyboard_double_arrow_right Article , Other literature type 2019Publisher:Springer Science and Business Media LLC Mukhtar Ahmed; Claudio O. Stöckle; Roger Nelson; Stewart S. Higgins; Shakeel Ahmad; Muhammad Ali Raza;pmid: 31127159
pmc: PMC6534615
AbstractElevated carbon-dioxide concentration [eCO2] is a key climate change factor affecting plant growth and yield. Conventionally, crop modeling work has evaluated the effect of climatic parameters on crop growth, without considering CO2. It is conjectured that a novel multimodal ensemble approach may improve the accuracy of modelled responses to eCO2. To demonstrate the applicability of a multimodel ensemble of crop models to simulation of eCO2, APSIM, CropSyst, DSSAT, EPIC and STICS were calibrated to observed data for crop phenology, biomass and yield. Significant variability in simulated biomass production was shown among the models particularly at dryland sites (44%) compared to the irrigated site (22%). Increased yield was observed for all models with the highest average yield at dryland site by EPIC (49%) and lowest under irrigated conditions (17%) by APSIM and CropSyst. For the ensemble, maximum yield was 45% for the dryland site and a minimum 22% at the irrigated site. We concluded from our study that process-based crop models have variability in the simulation of crop response to [eCO2] with greater difference under water-stressed conditions. We recommend the use of ensembles to improve accuracy in modeled responses to [eCO2].
https://doi.org/10.1... arrow_drop_down https://doi.org/10.1038/s41598...Article . 2019 . Peer-reviewedLicense: CC BYData 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.Access RoutesGreen gold 51 citations 51 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert https://doi.org/10.1... arrow_drop_down https://doi.org/10.1038/s41598...Article . 2019 . Peer-reviewedLicense: CC BYData 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.description Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type 2017Publisher:Springer Science and Business Media LLC Funded by:ANR | VIRGOANR| VIRGOAuthors: Mathias, Jean-Denis; Anderies, J.M.; Janssen, M.A.;AbstractThe planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO2 concentration of 550 ppm until 2100 and (2) returning to 350 ppm in 2100. Our results enable decision makers to assess the following milestones: (1) a minimum of 33% reduction of CO2 emissions by 2055 in order to stay below 550 ppm by 2100 (this milestone goes up to 46% in the case of delayed policies); and (2) carbon neutrality and the effective implementation of innovative geoengineering technologies (10% negative emissions) before 2060 in order to return to 350 ppm in 2100, under the assumption of getting out of the baseline scenario without delay. Finally, we emphasize the need to use adaptive path-based approach instead of single point target for climate policy design.
Arizona State Univer... arrow_drop_down Arizona State University: ASU Digital RepositoryArticle . 2017License: CC BYFull-Text: http://hdl.handle.net/2286/R.I.44365Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.1038/srep42...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefInstitut National de la Recherche Agronomique: ProdINRAArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)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.Access RoutesGreen gold 24 citations 24 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Arizona State Univer... arrow_drop_down Arizona State University: ASU Digital RepositoryArticle . 2017License: CC BYFull-Text: http://hdl.handle.net/2286/R.I.44365Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.1038/srep42...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefInstitut National de la Recherche Agronomique: ProdINRAArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)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.description Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type 2020Publisher:Copernicus GmbH Giorgia Bagagiolo; Danilo Rabino; Marcella Biddoccu; Guido Nigrelli; Daniele Cat Berro; Luca Mercalli; Federico Spanna; Giorgio Capello; Eugenio Cavallo;<p>Historical weather data represent an extremely precious resource for agro-meteorology for studying evolutionary dynamics and for predictive purposes, to address agronomical and management choices, that have economic, social and environmental effect. The study of climatic variability and its consequences starts from the observation of variations over time and the identification of the causes, on the basis of historical series of meteorological observations. The availability of long-lasting, complete and accurate datasets is a fundamental requirement to predict and react to climate variability. Inter-annual climate changes deeply affect grapevine productive cycle determining direct impact on the onset and duration of phenological stages and, ultimately, on the grape harvest and yield. Indeed, climate variables, such as air temperature and precipitation, affect evapotranspiration rates, plant water requirements, and also the vine physiology. In this respect, the observed increase in the number of warm days poses a threat to grape quality as it creates a situation of imbalance at maturity, with respect to sugar content, acidity and phenolic and aromatic ripeness.</p><p>A study was conducted to investigate the relationships between climate variables and harvest onset dates to assess the responses of grapevine under a global warming scenario. The study was carried out in the &#8220;Monferrato&#8221; area, a rainfed hillslope vine-growing area of NW Italy. In particular, the onset dates of harvest of different local wine grape varieties grown in the Vezzolano Experimental Farm (CNR-IMAMOTER) and in surrounding vineyards (affiliated to the Terre dei Santi Cellars) were recorded from 1962 to 2019 and then related to historical series of climate data by means of regression analysis. The linear regression was performed based on the averages of maximum and minimum daily temperatures and sum of precipitation (1962&#8211;2019) calculated for growing and ripening season, together with a bioclimatic heat index for vineyards, the Huglin index. The climate data were obtained from two data series collected in the Experimental farm by a mechanical weather station (1962-2002) and a second series recorded (2002-2019) by an electro-mechanical station included in Piedmont Regional Agro-meteorological Network. Finally, a third long-term continuous series covering the period from 1962 to 2019, provided by Italian Meteorological Society was considered in the analysis.</p><p>The results of the study highlighted that inter-annual climate variability, with a general positive trend of temperature, significantly affects the ripening of grapes with a progressive anticipation of the harvest onset dates. In particular, all the considered variables excepted precipitation, resulted negatively correlated with the harvest onset date reaching a high level of significance (up to P< 0.001). Best results have been obtained for maximum temperature and Huglin index, especially by using the most complete dataset. The change ratios obtained using datasets including last 15 years were greater (in absolute terms) than results limited to the period 1962-2002, and also correlations have greater level of significance. The results indicated clearly the relationships between the temperature trend and the gradual anticipation of harvest and the importance of having long and continuous historical weather data series available.</p>
IRIS Cnr arrow_drop_down Publications Open Repository TOrinoArticle . 2021License: CC BY NC NDData sources: Publications Open Repository TOrinoItalian Journal of AgrometeorologyArticle . 2021 . Peer-reviewedLicense: CC BYData 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.Access RoutesGreen gold 6 citations 6 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert IRIS Cnr arrow_drop_down Publications Open Repository TOrinoArticle . 2021License: CC BY NC NDData sources: Publications Open Repository TOrinoItalian Journal of AgrometeorologyArticle . 2021 . Peer-reviewedLicense: CC BYData 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.description Publicationkeyboard_double_arrow_right Article 2022Publisher:MDPI AG Authors: Leijiao Ge; Jun Yan; Yonghui Sun; Zhongguan Wang;doi: 10.3390/en15114164
In recent years, the accelerating climate change and intensifying natural disasters have called for more renewable, resilient, and reliable energy from more distributed sources to more diversified consumers, resulting in a pressing need for advanced situational awareness of modern smart distribution systems [...]
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.Access Routesgold 2 citations 2 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.description Publicationkeyboard_double_arrow_right Article , Other literature type 2017Publisher:MDPI AG Baohua Xie; Jiangxin Gu; Junbao Yu; Guangxuan Han; Xunhua Zheng; Yu Xu; Haitao Lin;doi: 10.3390/atmos8100181
Land use changes from cropland to orchards in Eastern China have raised serious concerns about the regional nitrogen (N) cycle and greenhouse gas balance. We measured soil nitrous oxide (N2O) emissions and methane (CH4) uptake using manual static chambers in an apple orchard. The primary aims were to assess the effect of N fertilizer application on gas fluxes and quantify the site-specific N2O emission factor (EFd). Field experiments were arranged in a randomized block design with three N input rates (0, 800 and 2600/2000 kg N ha−1 year−1). We found that orchard soils were a negligible CH4 sink (−1.1 to −0.4 kg C ha−1 year−1). Annual N2O emissions responded positively to N input rates, ranging from 34.1 to 60.3 kg N ha−1 year−1. EFd ranged from 1.00% to 1.65% with a mean of 1.34%. The extremely large background emissions of N2O (34.1–34.3 kg N ha−1 year−1) most likely originated from nitrate accumulation in the soil profile because of historical overuse of N fertilizer. We conclude that (1) site-specific EFd is suitable for assessing regional direct N2O emissions from upland orchards; and (2) conventional fertilization regimes must be avoided, and reduced N input rates are recommended in the study region.
Atmosphere arrow_drop_down AtmosphereOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2073-4433/8/10/181/pdfData sources: Multidisciplinary Digital Publishing Instituteadd 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.Access Routesgold 23 citations 23 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert Atmosphere arrow_drop_down AtmosphereOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2073-4433/8/10/181/pdfData sources: Multidisciplinary Digital Publishing Instituteadd 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.description Publicationkeyboard_double_arrow_right Article 2023Publisher:Frontiers Media SA Funded by:EC | IntelCompEC| IntelCompPapadaki, Lydia; Stavridis, Charalampos; Koundouri, Phoebe; Grypari, Ioanna; Kazbek, Madina; Papageorgiou, Haris; Theodossiou, Nicolaos;The phenomena of climate change transcend all national and regional boundaries. To address this complex challenge, we must determine the areas of the country of interest, in this case, Greece, that have been most adversely affected by climate. Greece is surrounded by water, and a significant part of its GDP is derived from the marine and maritime industries, including tourism. Since the start of the IntelComp project, a Preparatory Living Lab (PLL) has been planned and delivered, feeding into the development of the IntelComp platform and the Living Lab on Climate Change Adaptation. The study's results lead to the conclusion that one of the most important challenges in tackling climate change is the decarbonisation challenge, specifically the shift to renewable energy sources and the investments that must be made. Several EU and national policy frameworks, including the European Green Deal, the Climate Law, the National Long-term Strategy for 2050 (on the Climate and Energy), highlight the decarbonisation as one of the major challenges in the climate change pledge. This will be the primary subject of the IntelComp climate change case study. PLLs also led to the identification of policy questions and useful data sources to aid the IntelComp project's launch. While previous research on co-production has primarily focused on involving citizens through public participation processes in order to gain their support, trust, and insights in structured decision-making processes, our approach opens a new channel for incorporating external knowledge into problem-solving processes. The IntelComp project will aid in policy development by providing pertinent tools co-developed with the final users that will provide insights and analysis in the field of STI (Science, Technology, Innovation) encompassing all of the Energy areas mentioned above.
Frontiers in Environ... arrow_drop_down Frontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefOnline Research Database In TechnologyArticle . 2023Data sources: Online Research Database In TechnologyFrontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedData sources: European Union Open Data Portaladd 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.Access RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
more_vert Frontiers in Environ... arrow_drop_down Frontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefOnline Research Database In TechnologyArticle . 2023Data sources: Online Research Database In TechnologyFrontiers in Environmental EconomicsArticle . 2023 . Peer-reviewedData sources: European Union Open Data Portaladd 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.description Publicationkeyboard_double_arrow_right Article 2016Publisher:Elsevier BV Zhao, Hong; Gao, Yang; Wang, Jian; Chen, Chi; Chen, Dengjie; Wang, Chen; Ciucci, Francesco;Abstract Egg yolk-derived P and N dual doped nano carbon capsules (PNCCs) have been synthesized and used as lithium ion battery anodes. The application of egg yolk as the carbon source is a new and environmental-friendly approach for biomass recycling. The reversible capacity of half cells made of PNCCs is as high as ~770 mA h g−1 at a current density of 0.5 A g−1 with considerable rate capacity and cycling stability. PNCCs show a capsule-like structure, which provide extra edges and active sites for lithium intercalation. The heteroatom doping also introduce defects and disorder, which increases the electrochemical activity and creates more active sites for lithium insertion.
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.40 citations 40 popularity Top 10% influence Top 10% 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.description Publicationkeyboard_double_arrow_right Article 2023Publisher:Elsevier BV Yong, Wang; Huachao, Xu; Ying, Li; Na, Lin; Peilong, Xu;pmid: 37586484
This study aims to introduce, conceptualize, and design a novel biomass/gasification-driven hybrid energy configuration. The proposed hybrid configuration has four subsystems: reformer solid oxide fuel cell (RSOFC), biomass/gasification, homogeneous charge compression ignition engine (HCCIE) plus waste heat recovery system (WHRS). RSOFC and HCCIE systems are embedded to generate electric energy. The syngas required for these two subsystems is captured from the biomass/gasification subsystem. In addition to generating electrical energy, fuel cell is responsible for providing combustible fuel to the HCCIE subsystem. The embedded engine in the system can improve the proposed configuration efficiency by increasing the rate of electrical energy production. In addition, the dissipated heat of fuel cell and engine subsystems is recovered by WHRS. The proposed energy configuration is evaluated and discussed from energetically, exergetically and exergoeconomic and environmental aspects to obtain a comprehensive feasibility study of the plant. The offered hybrid design has new component's structure and relationships that have not been reported in the publications. The analysis indicated that the proposed hybrid configuration is capable of generating approximately 1100 kW and 366.3 W of electric and thermal power, respectively, with the overall energetic and exergetic efficiencies of 69.4% and 52.1%. Exergoeconomic analysis results revealed that the specific fuel cost of the total proposed configuration was approximately 1.96 USD per GJ. In addition, compared to a coal and petroleum oil-based power generation plants, the proposed hybrid configuration can have approximately 2.75-fold and 97.7% lower CO2 emissions, sequentially. Besides, the proposed system can rival other similar biomass-driven designs.
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.7 citations 7 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.description Publicationkeyboard_double_arrow_right Article 2023Publisher:Elsevier BV Mazzeo D.; Leva S.; Matera N.; Kontoleon K. J.; Saboor S.; Pirouz B.; Elkadeem M. R.;handle: 20.500.11770/358598 , 11311/1243737
While traditional methods for modelling the thermal and electrical behaviour of photovoltaic (PV) modules rely on analytical and empirical techniques, machine learning is gaining interest as a way to reduce the time, expertise, and tools required by designers or experts while maintaining high accuracy and reliability. This research presents a data-driven machine learning tool based on artificial neural networks (ANNs) that can forecast yearly PV electricity directly at the optimal PV inclination angle without geographic restrictions and is valid for a wide range of electrical characteristics of PV modules. Additionally, empirical correlations were developed to easily determine the optimal PV inclination angle worldwide. The ANN algorithm, developed in Matlab, systematically and quantitatively summarizes the behaviour of eight PV modules in 48 worldwide climatic conditions. The algorithm’s applicability and robustness were proven by considering two different PV modules in the same 48 locations. Yearly climatic variables and electrical/thermal PV module parameters serve as input training data. The yearly PV electricity is derived using dynamic simulations in the TRNSYS environment, which is a simulation program primarily and extensively used in the fields of renewable energy engineering and building simulation for passive as well as active solar design. Multiple performance metrics validate that the ANN-based machine learning tool demonstrates high reliability and accuracy in the PV energy production forecasting for all weather conditions and PV module characteristics. In particular, by using 20 neurons, the highest value of R-square of 0.9797 and the lowest values of the root mean square error and coefficient of variance of 14.67 kWh and 3.8%, respectively, were obtained in the training phase. This high accuracy was confirmed in the ANN validation phase considering other PV modules. An R-square of 0.9218 and values of the root mean square error and coefficient of variance of 31.95 kWh and 7.8%, respectively, were obtained.The results demonstrate the algorithm’s vast potential to enhance the worldwide diffusion and economic growth of solar energy, aligned with the seventh sustainable development goal.
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.Access RoutesGreen gold 14 citations 14 popularity Top 10% influence Top 10% 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.description Publicationkeyboard_double_arrow_right Article 2019Publisher:Elsevier BV Authors: Lehtola, Timo; Zahedi, Ahmad;Abstract Solar energy and wind power supply are renewable, decentralised and intermittent electrical power supply methods that require energy storage. Integrating this renewable energy supply to the electrical power grid may reduce the demand for centralised production, making renewable energy systems more easily available to remote regions. Control systems optimise solar energy and wind power sources to supply renewable energy to the power grid. Vehicle to Grid (V2G) operations support intermittent production as battery storage. In V2G operations, electric power flows from the power grid to the battery storage and from the battery storage back to the power grid. The primary goal of this study is to improve the existing renewable energy supply to provide more reliable units in the power grid. We consider the V2G concept as an extension of the smart charging system allowing electric vehicles to be able to inject battery energy into the power grid, acting as distributed generators or energy storage systems. This review shows how parallel V2G storage and battery storage supports the power grid. Further, the review indicates that decentralised V2G battery storages will be included in future renewable energy systems.
Sustainable Energy T... arrow_drop_down Sustainable Energy Technologies and AssessmentsArticle . 2019 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefJames Cook University, Australia: ResearchOnline@JCUArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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.138 citations 138 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert Sustainable Energy T... arrow_drop_down Sustainable Energy Technologies and AssessmentsArticle . 2019 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefJames Cook University, Australia: ResearchOnline@JCUArticle . 2019Data sources: Bielefeld Academic Search Engine (BASE)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.
