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End date: 2024 × Start date: 2020 × Start date: 2020 × DDC: 550 × WGL Institute: ATB ×

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Now showing 1 - 3 of 3
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    Effectivity and Cost Efficiency of a Tax on Nitrogen Fertilizer to Reduce GHG Emissions from Agriculture
    (Basel : MDPI AG, 2020) Meyer-Aurich, Andreas; Nadi Karatay, Yusuf; Nausediene, Ausra; Kirschke, Dieter
    The use of nitrogen (N) fertilizer substantially contributes to greenhouse gas (GHG) emissions due to N2O emissions from agricultural soils and energy-intensive fertilizer manufacturing. Thus, a reduction of mineral N fertilizer use can contribute to reduced GHG emissions. Fertilizer tax is a potential instrument to provide incentives to apply less fertilizer and contribute to the mitigation of GHG emissions. This study provides model results based on a production function analysis from field experiments in Brandenburg and Schleswig-Holstein, with respect to risk aversion by calculating certainty equivalents for different levels of risk aversion. The model results were used to identify effective and cost-efficient options considering farmers’ risk aversion to reduce N fertilizer, and to compare the potential and cost of GHG mitigation with different N fertilizer tax schemes. The results show that moderate N tax levels are effective in reducing N fertilizer levels, and thus, in curbing GHG emissions at costs below 100 €/t CO2eq for rye, barley and canola. However, in wheat production, N tax has limited effects on economically optimal N use due to the effects of N fertilizer on crop quality, which affect the sale prices of wheat. The findings indicate that the level of risk aversion does not have a consistent impact on the reduction of N fertilizer with a tax, even though the level of N fertilizer use is generally lower for risk-averse agents. The differences in N fertilizer response might have an impact on the relative advantage of different crops, which should be taken into account for an effective implementation of a tax on N fertilizer.
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    Can Green Plants Mitigate Ammonia Concentration in Piglet Barns?
    (Basel : MDPI, 2021) Menardo, Simona; Berg, Werner; Grüneberg, Heiner; Jakob, Martina
    For animal welfare and for farmers’ health, the concentration of ammonia (NH3 ) in animal houses should be as low as possible. Plants can remove various atmospheric contaminants through the leaf stomata. This study examined the effect of ornamental plants installed inside a piglet barn on the NH3 concentration in the air. Gas measurements of the air in the ‘greened’ compartment (P) and a control compartment (CTR) took place over two measuring periods (summer–autumn and winter). Differences between the NH3 emissions were calculated based on the ventilation rates according to the CO2 balance. Fairly low mean NH3 concentrations between 2 and 4 ppm were measured. The NH3 emissions were about 20% lower (p < 0.01) in P than in CTR, in summer–autumn and in winter period. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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    Viticulture in the Laetanian Region (Spain) during the Roman Period: Predictive Modelling and Geomatic Analysis
    (Basel : MDPI AG, 2020) Stubert, Lisa; Oliveras, Antoni Martín i; Märker, Michael; Schernthanner, Harald; Vogel, Sebastian
    Geographic information system (GIS)-based predictive modelling is widely used in archaeology to identify suitable zones for ancient settlement locations and determine underlying factors of their distribution. In this study, we developed predictive models on Roman viticulture in the Laetanian Region (Hispania Citerior-Tarraconensis), using the location of 82 ancient wine-pressing facilities or torcularia as response variables and 15 topographical and 6 socio-economic cost distance datasets as predictor variables. Several predictor variable subsets were selected either by expert knowledge of similar studies or by using a semi-automatization algorithm based on statistical distribution metrics of the input data. The latter aims at simplifying modelling and minimizing the necessity of a priori knowledge. Both approaches predicted the distribution of archeological sites sufficiently well. However, the best prediction performance was obtained by an expert knowledge model utilizing a predictor variable combination based on recommendations on viticulture by Lucius Junius Moderatus Columella, the prominent ancient Roman agronomist. The results indicate that the accessibility of a location and its connectivity to trade routes and distribution centres, determined by terrain steepness, was decisive for the settlement of viticultural facilities. With the knowledge gained, the ancient cultivated area and number of wine-pressing facilities needed for processing the vineyard yields were extrapolated for the entire study region.