904 resultados para Bioenergy Crop
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The purpose of this research is to explore the disparity between the existing model-orientated bioenergy decision support system (DSS) functions and what is desired by practitioners, in particular bioenergy project developers. This research has compiled the published bioenergy project development models, to highlight the characteristics emphasised by academics. When contrasted against a UK practitioner’s perspective through the administration of a Likert style questionnaire, it is clear that the general DSS issues still persist. Finally, the research suggests how this ’theory-practice’ divide could be addressed. The research contribute
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Interest in bioenergy as a viable alternative to fossil fuels is increasing. This emergent sector is subject to a range of ambitious initiatives promoted by National Governments to generate energy from renewable sources. Transition to energy production from biomass still lacks a feasible infrastructure particularly from a supply chain and business perspective. Supply chain integration has not been studied widely providing a deficit in the literature and in practice. This paper presents results from a pilot study designed to identify attributes that helps optimise such supply chains. To consider this challenge it is important to identify those characteristics that integrate bioenergy supply chains and ascertain if they are distinct from those found in conventional energy models. In general terms the supply chain is defined by upstream at the point of origin of raw materials and downstream at the point of distribution to final customer. It remains to be seen if this is the case for bioenergy supply chains as there is an imbalance between knowledge and practice, even understanding the terminology. The initial pilot study results presented in the paper facilitates understanding the gap between general supply chain knowledge and what is practiced within bioenergy organisations. © 2014 Elsevier Ltd. All rights reserved.
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Community acceptance has been identified as one of the key requirements for a sustainable bioenergy project. However less attention has been paid to this aspect from developing nations and small projects perspective. Therefore this research examines the role of community acceptance for sustainable small scale bioenergy projects in India. While addressing the aim, this work identifies influence of community over bioenergy projects, major concerns of communities regarding bioenergy projects and factors influencing perceptions of communities about bioenergy projects. The empirical research was carried out on four bioenergy companies in India as case studies. It has been identified that communities have significant influence over bioenergy projects in India. Local air pollution, inappropriate storage of by-products and credibility of developer are identified as some of the important concerns. Local energy needs, benefits to community from bioenergy companies, level of trust on company and relationship between company and the community are some of the prime factors which influence community's perception on bioenergy projects. This research sheds light on important aspects related to community acceptance of bioenergy projects, and this information would help practitioners in understanding the community perceptions and take appropriate actions to satisfy them. © 2014 Elsevier Ltd.
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Bio energy is a renewable energy and a solution to the depleting fossil fuels. Bio energy such as heat, power and bio fuel is generated by conversion technologies using biomass for example domestic waste, root crops, forest residue and animal slurry. Pyrolysis, anaerobic digestion and combined heat and power engine are some examples of the technologies. Depending on the nature of a biomass, it can be treated with various technologies giving out some products, which can be further treated with other technologies and eventually converted into the final products as bio energy. The pathway followed by the biomass, technologies, intermediate products and bio energy in the conversion process is referred to as bio energy pathway. Identification of appropriate pathways optimizes the conversion process. Although there are various approaches to create or generate the pathways, there is still a need for a semantic approach to generate the pathways, which allow checking the consistency of the knowledge, and to share and extend the knowledge efficiently. This paper presents an ontology-based approach to automatic generation of the pathways for biomass to bio energy conversion, which exploits the definition and hierarchical structure of the biomass and technologies, their relationship and associated properties, and infers appropriate pathways. A case study has been carried out in a real-life scenario, the bio energy project for the North West of Europe (Bioen NW), which showed promising results.
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he push to widen participation in public consultation suggests social media as an additional mechanism through which to engage the public. Bioenergy companies need to build their capacity to communicate in these new media and to monitor the attitudes of the public and opposition organisations towards energy development projects. Design/methodology/approach This short paper outlines the planning issues bioenergy developments face and the main methods of communication used in the public consultation process in the UK. The potential role of social media in communication with stakeholders is identified. The capacity of sentiment analysis to mine opinions from social media is summarised, and illustrated using a sample of tweets containing the term ‘bioenergy’ Findings Social media have the potential to improve information flows between stakeholders and developers. Sentiment analysis is a viable Purpose The push to widen participation in public consultation suggests social media as an additional mechanism through which to engage the public. Bioenergy companies need to build their capacity to communicate in these new media and to monitor the attitudes of the public and opposition organisations towards energy development projects. Design/methodology/approach This short paper outlines the planning issues bioenergy developments face and the main methods of communication used in the public consultation process in the UK. The potential role of social media in communication with stakeholders is identified. The capacity of sentiment analysis to mine opinions from social media is summarised, and illustrated using a sample of tweets containing the term ‘bioenergy’ Findings Social media have the potential to improve information flows between stakeholders and developers. Sentiment analysis is a viable methodology, which bioenergy companies should be using to measure public opinion in the consultation process. Preliminary analysis shows promising results. Research limitations/implications Analysis is preliminary and based on a small dataset. It is intended only to illustrate the potential of sentiment analysis and not to draw general conclusions about the bioenergy sector. Originality/value Opinion mining, though established in marketing and political analysis, is not yet systematically applied as a planning consultation tool. This is a missed opportunity.
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This study presents a two stage process to determine suitable areas to grow fuel crops: i) FAO Agro Ecological Zones (AEZ) procedure is applied to four Indian states of different geographical characteristics; and ii) Modelling the growth of candidate crops with GEPIC water and nutrient model, which is used to determine potential yield of candidate crops in areas where irrigation water is brackish or soil is saline. Absence of digital soil maps, paucity of readily available climate data and knowledge of detailed requirements of candidate crops are some of the major problems, of which, a series of detailed maps will evaluate true potential of biofuels in India.
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A cikkben paneladatok segítségével a magyar gabonatermesztő üzemek 2001 és 2009 közötti technikai hatékonyságát vizsgáljuk. A technikai hatékonyság szintjének becslésére egy hagyományos sztochasztikus határok modell (SFA) mellett a látens csoportok modelljét (LCM) használjuk, amely figyelembe veszi a technológiai különbségeket is. Eredményeink arra utalnak, hogy a technológiai heterogenitás fontos lehet egy olyan ágazatban is, mint a szántóföldi növénytermesztés, ahol viszonylag homogén technológiát alkalmaznak. A hagyományos, azonos technológiát feltételező és a látens osztályok modelljeinek összehasonlítása azt mutatja, hogy a gabonatermesztő üzemek technikai hatékonyságát a hagyományos modellek alábecsülhetik. _____ The article sets out to analyse the technical efficiency of Hungarian crop farms between 2001 and 2009, using panel data and employing both standard stochastic frontier analysis and the latent class model (LCM) to estimate technical efficiency. The findings suggest that technological heterogeneity plays an important role in the crop sector, though it is traditionally assumed to employ homogenous technology. A comparison of standard SFA models that assumes the technology is common to all farms and LCM estimates highlights the way the efficiency of crop farms can be underestimated using traditional SFA models.
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Acknowledgements We are grateful to the United Kingdom Economic and Social Research Council Nexus Network for funding this work.
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Acknowledgement Construction and maintenance of the experiment system was funded by the state Special Fund for Agro-scientific Research in the Public Interest “Climate Change Impacts on Crop Production and Mitigation” under a grant number 200903003. This work was financially supported by Ministry of Science and Technology of China under a grant number 2012BAC19B01 and Department of Science and Technology of Jiangsu province under a grant number BK20150684. The international cooperation was funded by “111 project” (B12009) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). The contribution of Pete Smith was funded by the Chinese Ministry of Agriculture and the United Kingdom Department for Environment, Food and Rural Affairs (DEFRA) under UK-China Sustainable Agriculture Innovation Network (SAIN). The contribution of Timothy Filley was also funded by the state foreign expert agency under a project of Foreign High-end expert program. The authors thank Jiangsu Tianniang Agro-Technology Company Ltd. for the assistance in maintaining the experiment system.
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Acknowledgements We are grateful to the United Kingdom Economic and Social Research Council Nexus Network for funding this work.
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Acknowledgements This work is based on the Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial (ELUM) project, which was commissioned and funded by the Energy Technologies Institute (ETI). The authors are grateful to Niall McNamara (Centre for Ecology & Hydrology, Lancaster) for coordinating the project and to Dagmar Henner (University of Aberdeen) for project assistance. We are also grateful to staff at the ETI, particularly to Geraldine Newton-Cross, Geraint Evans and Hannah Evans for constructive advice and feedback, and to Jonathan Oxley for project support. The ELUM Software Package contains Ordnance Survey data © Crown copyright and database right 2012.
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Funded by UK's Biotechnology and Biological Sciences Research Council (BBSRC) Department for Environment, Food and Rural Affairs (DEFRA). Grant Number: LK0863 BBSRC strategic programme Grant on Energy Grasses & Bio-refining. Grant Number: BBS/E/W/10963A01 OPTIMISC. Grant Number: FP7-289159 WATBIO. Grant Number: FP7-311929 Innovate UK/BBSRC ‘MUST’. Grant Number: BB/N016149/1
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This work contributes to the ELUM (Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial) project, which was commissioned and funded by the Energy Technologies Institute (ETI). We acknowledge the E-OBS data set from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu).
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Acknowledgements We are grateful to the United Kingdom Economic and Social Research Council Nexus Network for funding this work.