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Author Sanz-Cobena, A.; Misselbrook, T.H.; Hernaiz, P.; Vallejo, A. doi  openurl
  Title (up) Impact of rainfall to the effectiveness of pig slurry shallow injection method for NH3 mitigation in a Mediterranean soil Type Journal Article
  Year 2019 Publication Atmospheric Environment Abbreviated Journal Atm. Environ.  
  Volume 216 Issue Pages 116913  
  Keywords ammonia; micrometeorological method; slurry incorporation; trade-offs; nitrous oxide; mediterranean agroecosystems; nitrous-oxide emissions; field-applied manure; organic fertilizers; ammonia emissions; methane emissions; N2O emissions; animal manures; management; losses; grassland  
  Abstract Ammonia emission from fertilized cropping systems is an important concern for stakeholders, particularly in regions with high livestock densities producing large amounts of manure. Application of pig slurries can result in very large losses of N through NH3 volatilization, thus decreasing the N use efficiency (NUE) of the applied manure. Shallow incorporation has been shown to significantly abate these losses. In this field study, we assessed the impact of contrasting weather conditions on the effectiveness of shallow injection to abate NH3 emissions from pig slurry application to a Mediterranean soil. As potential trade-offs of NH3 abatement, greenhouse gas emissions were also measured under conditions of high soil moisture. Compared with surface application of slurry, shallow injection effectively and significantly decreased NH3 losses independently of weather conditions, but reductions of NH3 emission were greater after heavy rainfall. In contrast, under these conditions, shallow injection triggered higher emissions of N2O and CH4. Our findings reinforce the idea that any single-pollutant abatement strategy needs to be designed and assessed in a regional context and considering potential trade-offs in the form of other pollutants.  
  Address 2020-06-08  
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  Area Expedition Conference  
  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5234  
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Author Özkan Gülzari, Ş.; Vosough Ahmadi, B.; Stott, A.W. url  doi
openurl 
  Title (up) Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway Type Journal Article
  Year 2018 Publication Preventive Veterinary Medicine Abbreviated Journal Preventive Veterinary Medicine  
  Volume 150 Issue Pages 19-29  
  Keywords Dairy cow; Dynamic programming; Greenhouse gas emissions intensity; Profitability; Subclinical mastitis; Whole farm modelling  
  Abstract Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subclinical mastitis as an exemplar to benchmark alternative scenarios against an economic optimum and adjusted herd structure to estimate the GHG emissions intensity associated with varying levels of disease. Five levels of somatic cell count (SCC) classes were considered namely 50,000 (i.e. SCC50), 200,000, 400,000, 600,000 and 800,000 cells/mL (milliliter) of milk. The effects of varying levels of SCC on milk yield reduction and consequential milk price penalties were used in a dynamic programming (DP) model that maximizes the profit per cow, represented as expected net present value, by choosing optimal animal replacement rates. The GHG emissions intensities associated with different levels of SCC were then computed using a farm-scale model (HolosNor). The total culling rates of both primiparous (PP) and multiparous (MP) cows for the five levels of SCC scenarios estimated by the model varied from a minimum of 30.9% to a maximum of 43.7%. The expected profit was the highest for cows with SCC200 due to declining margin over feed, which influenced the DP model to cull and replace more animals and generate higher profit under this scenario compared to SCC50. The GHG emission intensities for the PP and MP cows with SCC50 were 1.01 kg (kilogram) and 0.95 kg carbon dioxide equivalents (CO2e) per kg fat and protein corrected milk (FPCM), respectively, with the lowest emissions being achieved in SCC50. Our results show that there is a potential to reduce the farm GHG emissions intensity by 3.7% if the milk production was improved through reducing the level of SCC to 50,000 cells/mL in relation to SCC level 800,000 cells/mL. It was concluded that preventing and/or controlling subclinical mastitis consequently reduces the GHG emissions per unit of product on farm that results in improved profits for the farmers through reductions in milk losses, optimum culling rate and reduced feed and other variable costs. We suggest that further studies exploring the impact of a combination of diseases on emissions intensity are warranted.  
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  ISSN 0167-5877 ISBN Medium  
  Area Expedition Conference  
  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5181  
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Author Lotze-Campen, H.; von Lampe, M.; Kyle, P.; Fujimori, S.; Havlik, P.; van Meijl, H.; Hasegawa, T.; Popp, A.; Schmitz, C.; Tabeau, A.; Valin, H.; Willenbockel, D.; Wise, M. url  doi
openurl 
  Title (up) Impacts of increased bioenergy demand on global food markets: an AgMIP economic model intercomparison Type Journal Article
  Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.  
  Volume 45 Issue 1 Pages 103-116  
  Keywords energy demand; agricultural markets; general equilibrium modeling; partial equilibrium modeling; model comparison; greenhouse-gas emissions; land-use; energy; productivity; scenarios; policies; capture; storage; system  
  Abstract Integrated Assessment studies have shown that meeting ambitious greenhouse gas mitigation targets will require substantial amounts of bioenergy as part of the future energy mix. In the course of the Agricultural Model Intercomparison and Improvement Project (AgMIP), five global agro-economic models were used to analyze a future scenario with global demand for ligno-cellulosic bioenergy rising to about 100 ExaJoule in 2050. From this exercise a tentative conclusion can be drawn that ambitious climate change mitigation need not drive up global food prices much, if the extra land required for bioenergy production is accessible or if the feedstock, for example, from forests, does not directly compete for agricultural land. Agricultural price effects across models by the year 2050 from high bioenergy demand in an ambitious mitigation scenario appear to be much smaller (+5% average across models) than from direct climate impacts on crop yields in a high-emission scenario (+25% average across models). However, potential future scarcities of water and nutrients, policy-induced restrictions on agricultural land expansion, as well as potential welfare losses have not been specifically looked at in this exercise.  
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  ISSN 0169-5150 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, TradeM Approved no  
  Call Number MA @ admin @ Serial 4532  
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Author Molina-Herrera, S.; Haas, E.; Grote, R.; Kiese, R.; Klatt, S.; Kraus, D.; Kampffmeyer, T.; Friedrich, R.; Andreae, H.; Loubet, B.; Ammann, C.; Horvath, L.; Larsen, K.; Gruening, C.; Frumau, A.; Butterbach-Bahl, K. doi  openurl
  Title (up) Importance of soil NO emissions for the total atmospheric NOX budget of Saxony, Germany Type Journal Article
  Year 2017 Publication Atmospheric Environment Abbreviated Journal Atm. Environ.  
  Volume 152 Issue Pages 61-76  
  Keywords LandscapeDNDC; Model evaluation; NOX emissions; Soil emissions; Distributed modeling; Emission inventory; Nitric-Oxide Emissions; European Forest Soils; Nitrous-Oxide; N2O; Emissions; Agricultural Soils; Gas Emissions; Organic Soil; Trace Gases; Model; Fluxes  
  Abstract Soils are a significant source for the secondary greenhouse gas NO and assumed to be a significant source of tropospheric NOx in rural areas. Here we tested the LandscapeDNDC model for its capability to simulate magnitudes and dynamics of soil NO emissions for 22 sites differing in land use (arable, grassland and forest) and edaphic as well as climatic conditions. Overall, LandscapeDNDC simulated mean soil NO emissions agreed well with observations (r(2) = 0.82). However, simulated day to day variations of NO did only agree weakly with high temporal resolution measurements, though agreement between simulations and measurements significantly increased if data were aggregated to weekly, monthly and seasonal time scales. The model reproduced NO emissions from high and low emitting sites, and responded to fertilization (mineral and organic) events with pulse emissions. After evaluation, we linked the LandscapeDNDC model to a GIS database holding spatially explicit data on climate, land use, soil and management to quantify the contribution of soil biogenic NO emissions to the total NOx budget for the State of Saxony, Germany. Our calculations show that soils of both agricultural and forest systems are significant sources and contribute to about 8% (uncertainty range: 6 -13%) to the total annual tropospheric NO, budget for Saxony. However, the contributions of soil NO emission to total tropospheric NO, showed a high spatial variability and in some rural regions such as the Ore Mts., simulated soil NO emissions were by far more important than anthropogenic sources. (C) 2016 Elsevier Ltd. All rights reserved.  
  Address 2017-04-07  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1352-2310 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4943  
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Author Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R. url  openurl
  Title (up) Integrated assessment of crop productivity based on the food supply forecasting Type Journal Article
  Year 2016 Publication Agricultural Economics – Czech Abbreviated Journal Agricultural Economics – Czech  
  Volume 61 Issue 11 Pages 502-510  
  Keywords climate changes; decision-making tools; estimation of parameters; forecasted outputs; gamma distribution; predicting yields; climate-change; emissions scenarios; impacts; potato; yield; growth; policy; scale; water  
  Abstract Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies.  
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  Series Volume Series Issue Edition  
  ISSN 0139-570x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4644  
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