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    Nitrous oxide emissions from winter oilseed rape cultivation
    (Amsterdam [u.a.] : Elsevier, 2017) Ruser, Reiner; Fuß, Roland; Andres, Monique; Hegewald, Hannes; Kesenheimer, Katharina; Köbke, Sarah; Räbiger, Thomas; Quinones, Teresa Suarez; Augustin, Jürgen; Christen, Olaf; Dittert, Klaus; Kage, Henning; Lewandowski, Iris; Prochnow, Annette; Stichnothe, Heinz; Flessa, Heinz
    Winter oilseed rape (Brassica napus L., WOSR) is the major oil crop cultivated in Europe. Rapeseed oil is predominantly used for production of biodiesel. The framework of the European Renewable Energy Directive requires that use of biofuels achieves GHG savings of at least 50% compared to use of fossil fuel starting in 2018. However, N2O field emissions are estimated using emission factors that are not specific for the crop and associated with strong uncertainty. N2O field emissions are controlled by N fertilization and dominate the GHG balance of WOSR cropping due to the high global warming potential of N2O. Thus, field experiments were conducted to increase the data basis and subsequently derive a new WOSR-specific emission factor. N2O emissions and crop yields were monitored for three years over a range of N fertilization intensities at five study sites representative of German WOSR production. N2O fluxes exhibited the typical high spatial and temporal variability in dependence on soil texture, weather and nitrogen availability. The annual N2O emissions ranged between 0.24 kg and 5.48 kg N2O-N ha−1 a−1. N fertilization increased N2O emissions, particularly with the highest N treatment (240 kg N ha−1). Oil yield increased up to a fertilizer amount of 120 kg N ha−1, higher N-doses increased grain yield but decreased oil concentrations in the seeds. Consequently oil yield remained constant at higher N fertilization. Since, yield-related emission also increased exponentially with N surpluses, there is potential for reduction of the N fertilizer rate, which offers perspectives for the mitigation of GHG emissions. Our measurements double the published data basis of annual N2O flux measurements in WOSR. Based on this extended dataset we modeled the relationship between N2O emissions and fertilizer N input using an exponential model. The corresponding new N2O emission factor was 0.6% of applied fertilizer N for a common N fertilizer amount under best management practice in WOSR production (200 kg N ha−1 a−1). This factor is substantially lower than the linear IPCC Tier 1 factor (EF1) of 1.0% and other models that have been proposed. © 2017
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    Ammonia and greenhouse gas emissions from slurry storage : A review
    (Amsterdam [u.a.] : Elsevier, 2020) Kupper, Thomas; Häni, Christoph; Neftel, Albrecht; Kincaid, Chris; Bühler, Marcel; Amon, Barbara; VanderZaag, Andrew
    Storage of slurry is an important emission source for ammonia (NH3), nitrous oxide (N2O), methane (CH4), carbon dioxide (CO2) and hydrogen sulfide (H2S) from livestock production. Therefore, this study collected published emission data from stored cattle and pig slurry to determine baseline emission values and emission changes due to slurry treatment and coverage of stores. Emission data were collected from 120 papers yielding 711 records of measurements conducted at farm-, pilot- and laboratory-scale. The emission data reported in a multitude of units were standardized and compiled in a database. Descriptive statistics of the data from untreated slurry stored uncovered revealed a large variability in emissions for all gases. To determine baseline emissions, average values based on a weighting of the emission data according to the season and the duration of the emission measurements were constructed using the data from farm-scale and pilot-scale studies. Baseline emissions for cattle and pig slurry stored uncovered were calculated. When possible, it was further distinguished between storage in tanks without slurry treatment and storage in lagoons which implies solid-liquid separation and biological treatment. The baseline emissions on an area or volume basis are: for NH3: 0.12 g m−2 h-1 and 0.15 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 0.08 g m−2 h-1 and 0.24 g m−2 h-1 for cattle and pig slurry stored in tanks; for N2O: 0.0003 g m−2 h-1 for cattle slurry stored in lagoons, and 0.002 g m−2 h-1 for both slurry types stored in tanks; for CH4: 0.95 g m-3 h-1 and 3.5 g m-3 h-1 for cattle and pig slurry stored in lagoons, and 0.58 g m-3 h-1 and 0.68 g m-3 h-1 for cattle and pig slurry stored in tanks; for CO2: 6.6 g m−2 h-1 and 0.3 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 8.0 g m−2 h-1 for both slurry types stored in tanks; for H2S: 0.04 g m−2 h-1 and 0.01 g m−2 h-1 for cattle and pig slurry stored in lagoons. Related to total ammoniacal nitrogen (TAN), baseline emissions for tanks are 16% and 15% of TAN for cattle and pig slurry, respectively. Emissions of N2O and CH4 relative to nitrogen (N) and volatile solids (VS) are 0.13% of N and 0.10% of N and 2.9% of VS and 4.7% of VS for cattle and pig slurry, respectively. Total greenhouse gas emissions from slurry stores are dominated by CH4. The records on slurry treatment using acidification show a reduction of NH3 and CH4 emissions during storage while an increase occurs for N2O and a minor change for CO2 as compared to untreated slurry. Solid-liquid separation causes higher losses for NH3 and a reduction in CH4, N2O and CO2 emissions. Anaerobically digested slurry shows higher emissions during storage for NH3 while losses tend to be lower for CH4 and little changes occur for N2O and CO2 compared to untreated slurry. All cover types are found to be efficient for emission mitigation of NH3 from stores. The N2O emissions increase in many cases due to coverage. Lower CH4 emissions occur for impermeable covers as compared to uncovered slurry storage while for permeable covers the effect is unclear or emissions tend to increase. Limited and inconsistent data regarding emission changes with covering stores are available for CO2 and H2S. The compiled data provide a basis for improving emission inventories and highlight the need for further research to reduce uncertainty and fill data gaps regarding emissions from slurry storage.
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    Sustainable food protein supply reconciling human and ecosystem health: A Leibniz Position
    (Amsterdam [u.a.] : Elsevier, 2020) Weindl, Isabelle; Ost, Mario; Wiedmer, Petra; Schreiner, Monika; Neugart, Susanne; Klopsch, Rebecca; Kühnhold, Holger; Kloas, Werner; Henkel, Ina M.; Schlüter, Oliver; Bußler, Sara; Bellingrath-Kimura, Sonoko D.; Ma, Hua; Grune, Tilman; Rolinski, Susanne; Klaus, Susanne
    Many global health risks are related to what and how much we eat. At the same time, the production of food, especially from animal origin, contributes to environmental change at a scale that threatens boundaries of a safe operating space for humanity. Here we outline viable solutions how to reconcile healthy protein consumption and sustainable protein production which requires a solid, interdisciplinary evidence base. We review the role of proteins for human and ecosystem health, including physiological effects of dietary proteins, production potentials from agricultural and aquaculture systems, environmental impacts of protein production, and mitigation potentials of transforming current production systems. Various protein sources from plant and animal origin, including insects and fish, are discussed in the light of their health and environmental implications. Integration of available knowledge is essential to move from a dual problem description (“healthy diets versus environment”) towards approaches that frame the food challenge of reconciling human and ecosystem health in the context of planetary health. This endeavor requires a shifting focus from metrics at the level of macronutrients to whole diets and a better understanding of the full cascade of health effects caused by dietary proteins, including health risks from food-related environmental degradation. © 2020
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    Measures to increase the nitrogen use efficiency of European agricultural production
    (Amsterdam [u.a.] : Elsevier, 2020) Hutchings, Nicholas J.; Sørensen, Peter; Cordovil, Cláudia M.d.S.; Leip, Adrian; Amon, Barbara
    Inputs of nitrogen to agricultural production systems are necessary to produce food, feed and fibre, but nitrogen (N) losses from those systems represent a waste of a resource and a threat to both the environment and human health. The nitrogen use efficiency (NUE) of an agricultural production system can be seen as an indicator of the balance between benefits and costs of primary food, feed and fibre production. Here, we used modelling to follow the fate of the virgin N input to different production systems (ruminant and granivore meat, dairy, arable), and to estimate their NUE at the system scale. We defined two ruminant meat production systems, depending on whether the land places constraints on farming practices. The other production systems were dairy, granivore and arable production on land without constraints. Two geographic regions were considered: Northern and Southern Europe. Measures to improve NUE were identified and allocated to Low, Medium and High ambition groups, with Low equating to the current situation in Europe for production systems that are broadly following good agricultural practice. The NUE of the production systems was similar to or higher in Southern than Northern Europe, with the maximum technical NUEs if all available measures are implemented were for North and South Europe, respectively, 82% and 92% for arable systems, 71% and 80% for granivores, 50% and 36% for ruminant meat production on constrained land, 53% and 55% for dairy production on unconstrained land and 46% and 62% for ruminant meat production on unconstrained land. The values for NUE found here tend to be higher than reported elsewhere, possibly due to the accounting for long-term residual effects of fertiliser and manure in our method. The greatest increase in NUE with the progressive implementation of higher ambition measures was in unconstrained granivore systems and the least was in constrained ruminant meat systems, reflecting the lower initial NUE of granivore systems and the larger number of measures applicable to confined livestock systems. Our work supports use of NUE as an indicator of the temporal trend in the costs and benefits of existing agricultural production systems, but highlights problems associated with its use as a sustainability criteria for livestock production systems. For arable systems, we consider well-founded the NUE value of 90% above which there is a high risk of soil N depletion, provided many measures to increase NUE are employed. For systems employing fewer measures, we suggest a value of 70% would be more appropriate. We conclude that while it is feasible to calculate the NUE of livestock production systems, the additional complexity required reduces its value as an indicator for benchmarking sustainability in practical agriculture. © 2020 The Authors
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    Prediction of the biogas production using GA and ACO input features selection method for ANN model
    (Amsterdam [u.a.] : Elsevier, 2019) Beltramo, Tanja; Klocke, Michael; Hitzmann, Bernd
    This paper presents a fast and reliable approach to analyze the biogas production process with respect to the biogas production rate. The experimental data used for the developed models included 15 process variables measured at an agricultural biogas plant in Germany. In this context, the concentration of volatile fatty acids, total solids, volatile solids acid detergent fibre, acid detergent lignin, neutral detergent fibre, ammonium nitrogen, hydraulic retention time, and organic loading rate were used. Artificial neural networks (ANN) were established to predict the biogas production rate. An ant colony optimization and genetic algorithms were implemented to perform the variable selection. They identified the significant process variables, reduced the model dimension and improved the prediction capacity of the ANN models. The best prediction of the biogas production rate was obtained with an error of prediction of 6.24% and a coefficient of determination of R2 = 0.9.
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    CFD modelling of an animal occupied zone using an anisotropic porous medium model with velocity depended resistance parameters
    (Amsterdam [u.a.] : Elsevier, 2021) Doumbia, E. Moustapha; Janke, David; Yi, Qianying; Amon, Thomas; Kriegel, Martin; Hempel, Sabrina
    The airflow in dairy barns is affected by many factors, such as the barn’s geometry, weather conditions, configurations of the openings, cows acting as heat sources, flow obstacles, etc. Computational fluids dynamics (CFD) has the advantages of providing detailed airflow information and allowing fully-controlled boundary conditions, and therefore is widely used in livestock building research. However, due to the limited computing power, numerous animals are difficult to be designed in detail. Consequently, there is the need to develop and use smart numerical models in order to reduce the computing power needed while at the same time keeping a comparable level of accuracy. In this work the porous medium modeling is considered to solve this problem using Ansys Fluent. A comparison between an animal occupied zone (AOZ) filled with randomly arranged 22 simplified cows’ geometry model (CM) and the porous medium model (PMM) of it, was made. Anisotropic behavior of the PMM was implemented in the porous modeling to account for turbulence influences. The velocity at the inlet of the domain has been varied from 0.1 m s−1 to 3 m s−1 and the temperature difference between the animals and the incoming air was set at 20 K. Leading to Richardson numbers Ri corresponding to the three types of heat transfer convection, i.e. natural, mixed and forced convection. It has been found that the difference between two models (the cow geometry model and the PMM) was around 2% for the pressure drop and less than 6% for the convective heat transfer. Further the usefulness of parametrized PMM with a velocity adaptive pressure drop and heat transfer coefficient is shown by velocity field validation of an on-farm measurement.