Suchergebnisse

Agricultural activities are important sources of atmospheric nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2). In the European Union, the agricultural sector contributes approximately 10% of the total emitted greenhouse gases (GhG). We search for evaluating GhG emissions at the farm level and designing mitigation options from a biotechnical point of view. As GhG emissions occur at several stages within the farm operation, it is essential to combine nutrient cycling and farm working through an integrated farm approach to reach a full accounting of processes. Our proposal comprises the following characteristics:- Our whole farm approach (FarmSim) combines empirical and mechanistic modelling through describing of above and below ground C and N fluxes; with respect to GhG, emissions can be also calculated with emissions factors, comparable to the IPCC methodology when no model is available yet as for manure management for instance. - Rebuilding farmers' practices description from available data (on farm and through farms'network databases) needs to choose a level of information to translate real situations to generic ones. It requires thus to choose a set of farm components and compatible spatio-temporal scales in respect with the data needed by the models. - At the moment, we coupled tow models allowing to quantify the emissions of the different lend uses (in our case PaSim, a grassland ecosystem model and CERES-EGC, a crop model). - The system boundaries are limited to the farm gate, or may include pre- and post-chain effects according to more and less high inputs and the difficulty to forecast produce fate if databases are available. - Building plausible scenarios requires to control a set farm operation coherences to account for stranding mitigation options. In a first step, we used a case study formalized by the French Livestock Institute (IE) and some farm working data from an experimental dairy farm belonging to the French Institute for Agricultural Research (INRA), both located in semi-continental conditions (Mirecourt-North-Eastern France). The simulated farming system is a mixed dairy and crops system so as to account for a rather generic farming system.

Agricultural activities are important sources of atmospheric nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2). In the European Union, the agricultural sector contributes approximately 10% of the total emitted greenhouse gases (GhG). We search for evaluating GhG emissions at the farm level and designing mitigation options from a biotechnical point of view. As GhG emissions occur at several stages within the farm operation, it is essential to combine nutrient cycling and farm working through an integrated farm approach to reach a full accounting of processes. Our proposal comprises the following characteristics: - Our whole farm approach (FarmSim) combines empirical and mechanistic modelling through describing of above and below ground C and N fluxes; with respect to GhG, emissions can be also calculated with emissions factors, comparable to the IPCC methodology when no model is available yet as for manure management for instance. - Rebuilding farmers' practices description from available data (on farm and through farms'network databases) needs to choose a level of information to translate real situations to generic ones. It requires thus to choose a set of farm components and compatible spatio-temporal scales in respect with the data needed by the models. - At the moment, we coupled tow models allowing to quantify the emissions of the different lend uses (in our case PaSim, a grassland ecosystem model and CERES-EGC, a crop model). - The system boundaries are limited to the farm gate, or may include pre- and post-chain effects according to more and less high inputs and the difficulty to forecast produce fate if databases are available. - Building plausible scenarios requires to control a set farm operation coherences to account for stranding mitigation options. In a first step, we used a case study formalized by the French Livestock Institute (IE) and some farm working data from an experimental dairy farm belonging to the French Institute for Agricultural Research (INRA), both located in semi-continental conditions (Mirecourt-North-Eastern France). The simulated farming system is a mixed dairy and crops system so as to account for a rather generic farming system.

Agricultural activities are important sources of atmospheric nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2). In the European Union, the agricultural sector contributes approximately 10% of the total emitted greenhouse gases (GhG). We search for evaluating GhG emissions at the farm level and designing mitigation options from a biotechnical point of view. As GhG emissions occur at several stages within the farm operation, it is essential to combine nutrient cycling and farm working through an integrated farm approach to reach a full accounting of processes. Our proposal comprises the following characteristics:- Our whole farm approach (FarmSim) combines empirical and mechanistic modelling through describing of above and below ground C and N fluxes; with respect to GhG, emissions can be also calculated with emissions factors, comparable to the IPCC methodology when no model is available yet as for manure management for instance. - Rebuilding farmers' practices description from available data (on farm and through farms'network databases) needs to choose a level of information to translate real situations to generic ones. It requires thus to choose a set of farm components and compatible spatio-temporal scales in respect with the data needed by the models. - At the moment, we coupled tow models allowing to quantify the emissions of the different lend uses (in our case PaSim, a grassland ecosystem model and CERES-EGC, a crop model). - The system boundaries are limited to the farm gate, or may include pre- and post-chain effects according to more and less high inputs and the difficulty to forecast produce fate if databases are available. - Building plausible scenarios requires to control a set farm operation coherences to account for stranding mitigation options. In a first step, we used a case study formalized by the French Livestock Institute (IE) and some farm working data from an experimental dairy farm belonging to the French Institute for Agricultural Research (INRA), both located in ...

submitted to Renewable and Sustainable Energy Reviews ; International audience ; Meeting future policy targets for bioenergy development worldwide poses major challenges for biomass feedstock supply chains in terms of competitiveness, reliability and sustainability. This paper reviews current knowledge on the sustainability of agricultural feedstock supply chains and emphasize future research needs. It covers annual and perennial feedstocks, and environmental, economic and social aspects. Knowledge gaps and technological options to assess and meet sustainability criteria are reviewed from plot to landscape and global scales. Bioenergy feedstocks present a wide range of dry matter yields, agricultural input requirements and environmental impacts, depending on crop type, management practices, and soil and climate conditions. Their integration into farmers' cropping systems poses specific challenges in terms of environmental impacts, but also opportunities for improvements via the use of grass-legume intercropping or residues from biomass conversion processes. Taking into account the spatial distribution of bioenergy crops is paramount to assessing their environmental impacts, in particular on biodiversity, or the food versus energy competition issue. However, few modelling frameworks convey the full complexity of the underlying processes and drivers, whether economic, social or biophysical. In particular, social impacts of bioenergy projects are seldom assessed and there is no methodological consensus. The main research areas identified involve: multi-crop and multi-site experiments, along with modelling, to optimise management practices and cropping systems producing bioenergy, possibly on alternative lands and under future climate changes; the design of innovative cropping systems using expert knowledge to ensure suitable integration into farmers' cropping systems; the collection of detailed data on the location of bioenergy crops to validate theoretical modelling frameworks and improve sustainability ...

submitted to Renewable and Sustainable Energy Reviews ; International audience ; Meeting future policy targets for bioenergy development worldwide poses major challenges for biomass feedstock supply chains in terms of competitiveness, reliability and sustainability. This paper reviews current knowledge on the sustainability of agricultural feedstock supply chains and emphasize future research needs. It covers annual and perennial feedstocks, and environmental, economic and social aspects. Knowledge gaps and technological options to assess and meet sustainability criteria are reviewed from plot to landscape and global scales. Bioenergy feedstocks present a wide range of dry matter yields, agricultural input requirements and environmental impacts, depending on crop type, management practices, and soil and climate conditions. Their integration into farmers' cropping systems poses specific challenges in terms of environmental impacts, but also opportunities for improvements via the use of grass-legume intercropping or residues from biomass conversion processes. Taking into account the spatial distribution of bioenergy crops is paramount to assessing their environmental impacts, in particular on biodiversity, or the food versus energy competition issue. However, few modelling frameworks convey the full complexity of the underlying processes and drivers, whether economic, social or biophysical. In particular, social impacts of bioenergy projects are seldom assessed and there is no methodological consensus. The main research areas identified involve: multi-crop and multi-site experiments, along with modelling, to optimise management practices and cropping systems producing bioenergy, possibly on alternative lands and under future climate changes; the design of innovative cropping systems using expert knowledge to ensure suitable integration into farmers' cropping systems; the collection of detailed data on the location of bioenergy crops to validate theoretical modelling frameworks and improve sustainability ...

submitted to Renewable and Sustainable Energy Reviews ; International audience ; Meeting future policy targets for bioenergy development worldwide poses major challenges for biomass feedstock supply chains in terms of competitiveness, reliability and sustainability. This paper reviews current knowledge on the sustainability of agricultural feedstock supply chains and emphasize future research needs. It covers annual and perennial feedstocks, and environmental, economic and social aspects. Knowledge gaps and technological options to assess and meet sustainability criteria are reviewed from plot to landscape and global scales. Bioenergy feedstocks present a wide range of dry matter yields, agricultural input requirements and environmental impacts, depending on crop type, management practices, and soil and climate conditions. Their integration into farmers' cropping systems poses specific challenges in terms of environmental impacts, but also opportunities for improvements via the use of grass-legume intercropping or residues from biomass conversion processes. Taking into account the spatial distribution of bioenergy crops is paramount to assessing their environmental impacts, in particular on biodiversity, or the food versus energy competition issue. However, few modelling frameworks convey the full complexity of the underlying processes and drivers, whether economic, social or biophysical. In particular, social impacts of bioenergy projects are seldom assessed and there is no methodological consensus. The main research areas identified involve: multi-crop and multi-site experiments, along with modelling, to optimise management practices and cropping systems producing bioenergy, possibly on alternative lands and under future climate changes; the design of innovative cropping systems using expert knowledge to ensure suitable integration into farmers' cropping systems; the collection of detailed data on the location of bioenergy crops to validate theoretical modelling frameworks and improve sustainability ...

VTT Tiedotteita - Research Notes 2441 ; The study carried out within the Bioenergy Network of Excellence analyses the implementation of important EU directives and policies relating to bioenergy in Europe to identify major RD&D needs in the field. Major EU directives, commonly known as the Promotion of Renewable Electricity, Biofuels and Landfill Directives, along with the EU Emissions Trading Scheme and parts of the Common Agricultural Policy, are some of the most important drivers behind the growth of bioenergy in the EU27 today. The report compares how Germany, Finland and the Netherlands have implemented the directives, examining the policy frameworks in each country and the plans and mechanisms in place to reach national targets. A wider European perspective for each directive is then drawn out, and recommendations for RD&D actions to meet the EU directive targets or obligations in each area are outlined. The report also takes a broader look at the effects the EU Emissions Trading Scheme and the Common Agricultural Policy are having on the use of biomass in the EU with RD&D recommendations for each area. Bioenergy NoE advocates stronger communication and co-operation among various EU-wide projects and initiatives focusing on bioenergy development. Industry commitment to RD&D projects is, however, the only direct path for bringing state-of-the-art technology and products to market. Building sustainable production pathways and addressing competition with food products is crucial to developing environmentally-sound biofuels. Research in renewable electricity from biomass should prioritize development of higher efficiency power production and power-to-heat ratios in combined heat and power plants over new technology development. In the biofuels field, RD&D should prioritize the development of more sustainable, second generation biofuels. To meet landfill diversion targets, thermal conversion and energy recovery of municipal solid waste in some EU countries will have to increase. Meeting the European targets set for 2020 requires significant technology development in order to introduce a new generation of biofuels and feedstocks: this is the focus for Bioenergy NoE RD&D.

Des chaînes d'approvisionnement en biomasse respectueuses de l'environnement et économiquement compétitives sont un facteur clé de succès pour le développement de la bio-économie. Or Celui-ci est susceptible d'être entravé par la pénurie potentielle de biomasse lignocellulosique, matière première la plus demandée pour fabriquer des produits bio-sources. Des technologies innovantes pour la gestion des cultures, la récolte de biomasse et leur prétraitement, le stockage et le transport offrent de nombreuses possibilités pour augmenter l'offre en biomasse tout en réduisant les coûts et en minimisant les impacts négatifs sur l'environnement. Trois récents projets européens visaient à développer de telles technologies, l'ensemble des chaînes logistiques, et à évaluer leur viabilité et durabilité. Les sources de biomasse étudiées incluaient les rémanents forestiers, les résidus d'arboriculture ainsi que des cultures lignocellulosiques annuelles, pérennes et ligneuses. Des filières existantes dans différentes régions d'Europe ont servi de cas d'étude en vraie grandeur et de support pour des démonstrations à l'échelle commerciale. Les principaux verrous identifiés concernent le stockage de biomasse et la phase de production pour les cultures dédiées, et des leviers d'amélioration portant sur la densification de la biomasse, le développement de systèmes de récolte plus efficaces et les systèmes de production de biomasse ont permis de réduire les coûts, la consommation d'énergie et les émissions de gaz à effet de serre. ; Cost-efficient, environmental-friendly and socially sustainable biomass supply chains are urgently needed to achieve the 2020 and 2030 targets of the European Union. Optimized logistics are a key factor of success for bio-based value-chains, and there is currently ample room for improvement. Innovative techniques for crop management, biomass harvesting and pre-treatment, storage and transport offer a prime avenue to increase biomass supply while keeping costes down and minimizing adverse environmental impacts. This communication will draw on results from recent projects funded by the European Commission on the development of new or improved technologies for logistics chains, encompassing energy crops, forest and agricultural residues. It includes an assessment of their sustainability at supply-area level for small to large-scale bio-based projects. The main bottlenecks of logistics reside in storage capacity and feedstock production, and some promising avenues to alleviate include legume-lignocellulosics mixtures, decentralized densification via briquetting, more efficient harversting systems and a widening of harvesting time windows. In a case-study in Burgundy, reduction in costs of more than 30% could be achieved with these options, along with an abatement of 10 to 20 % of greenhouse gas emissions.

Une des attentes forte de la société et des décideurs politiques est de mieux comprendre et de pouvoir anticiper les réponses des agro-écosystèmes aux changements climatiques et atmosphériques anticipés. La prévision sur le long-terme de ces impacts sur la contribution des agro-écosystèmes à l'effet de serre et sur leur potentiel d'atténuation des émissions permis par le stockage de carbone dans la matière organique des sols repose nécessairement sur l'utilisation de modèles. PaSiM est un modèle biogéochimique déterministe à dominante mécaniste se situant à l'échelle de la parcelle de prairie et qui a pour objectif principal de modéliser une prairie spatialement homogène et ses principaux flux de carbone, d'azote et d'eau. Au-delà de cette modélisation "prairie centrée", le modèle FarmSim permet de simuler le comportement de systèmes d'élevage herbagers ou basés sur le maïs à l'échelle de la ferme. Résultant du couplage des modèles PaSiM, CERES (culture) et GESTIM (intrants, calcul des flux à l'étable) il fournit un bilan annuel des émissions de GES à l'échelle de l'exploitation. Ce papier se propose de décrire ces deux modèles et l'intérêt qu'ils présentent pour répondre aux attentes sociales vis-à-vis des impacts du changement climatique sur les prairies et les systèmes d'élevage

Une des attentes forte de la société et des décideurs politiques est de mieux comprendre et de pouvoir anticiper les réponses des agro-écosystèmes aux changements climatiques et atmosphériques anticipés. La prévision sur le long-terme de ces impacts sur la contribution des agro-écosystèmes à l'effet de serre et sur leur potentiel d'atténuation des émissions permis par le stockage de carbone dans la matière organique des sols repose nécessairement sur l'utilisation de modèles. PaSiM est un modèle biogéochimique déterministe à dominante mécaniste se situant à l'échelle de la parcelle de prairie et qui a pour objectif principal de modéliser une prairie spatialement homogène et ses principaux flux de carbone, d'azote et d'eau. Au-delà de cette modélisation "prairie centrée", le modèle FarmSim permet de simuler le comportement de systèmes d'élevage herbagers ou basés sur le maïs à l'échelle de la ferme. Résultant du couplage des modèles PaSiM, CERES (culture) et GESTIM (intrants, calcul des flux à l'étable) il fournit un bilan annuel des émissions de GES à l'échelle de l'exploitation. Ce papier se propose de décrire ces deux modèles et l'intérêt qu'ils présentent pour répondre aux attentes sociales vis-à-vis des impacts du changement climatique sur les prairies et les systèmes d'élevage

Une des attentes forte de la société et des décideurs politiques est de mieux comprendre et de pouvoir anticiper les réponses des agro-écosystèmes aux changements climatiques et atmosphériques anticipés. La prévision sur le long-terme de ces impacts sur la contribution des agro-écosystèmes à l'effet de serre et sur leur potentiel d'atténuation des émissions permis par le stockage de carbone dans la matière organique des sols repose nécessairement sur l'utilisation de modèles. PaSiM est un modèle biogéochimique déterministe à dominante mécaniste se situant à l'échelle de la parcelle de prairie et qui a pour objectif principal de modéliser une prairie spatialement homogène et ses principaux flux de carbone, d'azote et d'eau. Au-delà de cette modélisation "prairie centrée", le modèle FarmSim permet de simuler le comportement de systèmes d'élevage herbagers ou basés sur le maïs à l'échelle de la ferme. Résultant du couplage des modèles PaSiM, CERES (culture) et GESTIM (intrants, calcul des flux à l'étable) il fournit un bilan annuel des émissions de GES à l'échelle de l'exploitation. Ce papier se propose de décrire ces deux modèles et l'intérêt qu'ils présentent pour répondre aux attentes sociales vis-à-vis des impacts du changement climatique sur les prairies et les systèmes d'élevage

Une des attentes forte de la société et des décideurs politiques est de mieux comprendre et de pouvoir anticiper les réponses des agro-écosystèmes aux changements climatiques et atmosphériques anticipés. La prévision sur le long-terme de ces impacts sur la contribution des agro-écosystèmes à l'effet de serre et sur leur potentiel d'atténuation des émissions permis par le stockage de carbone dans la matière organique des sols repose nécessairement sur l'utilisation de modèles. PaSiM est un modèle biogéochimique déterministe à dominante mécaniste se situant à l'échelle de la parcelle de prairie et qui a pour objectif principal de modéliser une prairie spatialement homogène et ses principaux flux de carbone, d'azote et d'eau. Au-delà de cette modélisation "prairie centrée", le modèle FarmSim permet de simuler le comportement de systèmes d'élevage herbagers ou basés sur le maïs à l'échelle de la ferme. Résultant du couplage des modèles PaSiM, CERES (culture) et GESTIM (intrants, calcul des flux à l'étable) il fournit un bilan annuel des émissions de GES à l'échelle de l'exploitation. Ce papier se propose de décrire ces deux modèles et l'intérêt qu'ils présentent pour répondre aux attentes sociales vis-à-vis des impacts du changement climatique sur les prairies et les systèmes d'élevage ; One of the expectations of society and stakeholders is to better understand and anticipate agroecosystems responses to atmospheric and climatic changes. Modelling is required to predict long-term climate change impacts on the greenhouse gas (GHG) balance of these ecosystems and their GHG mitigation potental through soil C sequestration. PaSiM is a grassland biogeochimical deterministic and mechanistic model, that assumes homogeneous vegetation and that simulates at plot scale grassland main carbon, nitrogen and water fluxes. At a larger scale, FarmSim couples the models PASIM, CERES (crop) and GESTIM (inputs, fluxes at barn) to make an assessment of GHG balance at the farm level. This paper aims at describing these two models to show in what extent they are useful tools in climate change impact studies on grassland and pasture-based livestock systems

Une des attentes forte de la société et des décideurs politiques est de mieux comprendre et de pouvoir anticiper les réponses des agro-écosystèmes aux changements climatiques et atmosphériques anticipés. La prévision sur le long-terme de ces impacts sur la contribution des agro-écosystèmes à l'effet de serre et sur leur potentiel d'atténuation des émissions permis par le stockage de carbone dans la matière organique des sols repose nécessairement sur l'utilisation de modèles. PaSiM est un modèle biogéochimique déterministe à dominante mécaniste se situant à l'échelle de la parcelle de prairie et qui a pour objectif principal de modéliser une prairie spatialement homogène et ses principaux flux de carbone, d'azote et d'eau. Au-delà de cette modélisation "prairie centrée", le modèle FarmSim permet de simuler le comportement de systèmes d'élevage herbagers ou basés sur le maïs à l'échelle de la ferme. Résultant du couplage des modèles PaSiM, CERES (culture) et GESTIM (intrants, calcul des flux à l'étable) il fournit un bilan annuel des émissions de GES à l'échelle de l'exploitation. Ce papier se propose de décrire ces deux modèles et l'intérêt qu'ils présentent pour répondre aux attentes sociales vis-à-vis des impacts du changement climatique sur les prairies et les systèmes d'élevage