Search

The potential of nitrogen (N) fertilizer forms to mitigate N 2 O emissions from agricultural fields is not very well understood. It is known that both reduced and oxidized N forms can be beneficial, depending on site-specific edaphic and climatic conditions. In the present study four laboratory incubation experiments were conducted under conditions that should minimize denitrification to investigate N 2 O emissions during the nitrification of solid N fertilizers. It was found that on two loamy sand soils with pH values slightly above pH 5, urea caused 2.7–3.8 fold higher cumulative N 2 O emissions than ammonium sulphate (AS). N 2 O emission rates from urea were accompanied by elevated soil nitrite levels, while those of AS were not. The direct addition of a NaNO 2 solution revealed an exponential relationship between soil nitrite levels and cumulative N 2 O emissions, indicating that soil nitrite induces N 2 O emissions, probably by nitrite reduction via nitrifier denitrification. When the soil pH was increased to 6.3 (soil from a long-term liming experiment) nitrite accumulation during nitrification was observed for both N forms. Cumulative N 2 O emissions did not differ between N forms on the latter soil, but N 2 O emission kinetics were faster for urea. Cumulative N 2 O emissions from AS at soil pH 6.3 were significantly higher than those of AS at pH values around 5. It was concluded that i) nitrite accumulation during nitrification of reduced N fertilizer forms can significantly contribute to N 2 O emissions under non-denitrifying conditions, ii) the risk of nitrite accumulation increases with higher soil pH values, and iii) that the alkalizing hydrolysis of urea increases the risk of nitrite accumulation and thus higher N 2 O emissions as well. This mechanism would explain why urea causes higher N 2 O emissions than fertilizers in the form of ammonium salts.

In this work we demonstrate the superiority of the IDDES turbulence model approach compared to the RANS formulation at the application of a Francis pump turbine flow simulation at part load conditions. At this operating point strongly swirling flow occurs in the draft tube, which leads to the vortex rope phenomenon, a rotating vortex around the stagnant region in the centre of the diffuser flow leading to a local low pressure zone. This hybrid RANS-LES turbulence model approach – based on the SST turbulence model – was implemented in OpenFOAM®-1.6-ext open source code and successfully validated for different test cases, like the decay of isotropic turbulence, periodic channel flow, flow over an abrupt expansion and a periodic hill flow. With these test cases constants were calibrated, a good prediction of boundary layer flow was proven and the ability to predict the flow correctly for numerically more difficult flow configurations. The flow in the pump turbine draft tube was analysed with laser measurements (LDA and PIV) and wall pressure sensors, as well as torque, hydraulic head and discharge measurements. All measurements serve as validation for the flow simulations. The results of the flow simulations with the IDDES turbulence model fit quite well with the measurements for the velocity components and especially for the second order statistics. This means that the turbulence is well resolved. The shape of the vortex rope is better predicted, leading to better conformity with the measurements, even for high frequencies. The hybrid turbulence model resolves the inertial range of turbulence.

A new life cycle assessment (LCA) method is presented, which is specifically tailored to plant nutrition in arable crop production. Generally, LCA is a methodology to assess all environmental impacts associated with a product or a process by accounting and evaluating its resource consumption and emissions. In LCA studies the entire production system should be considered, i.e. for crop production systems the analysis includes not only the on-field activities, but also all impacts related to the production of raw materials (minerals, fossil fuels) and farm inputs like fertilizers, plant protection substances, machinery or seeds. The LCA method developed in this study evaluates the impact of emissions and resource consumption associated with crop production on the following environmental effects: depletion of abiotic resources, land use, climate change, toxicity, acidification, and eutrophication. In order to enable conclusions on the overall environmental impact of alternative crop nutrition systems, an aggregation procedure to calculate indicators for resource depletion (RDI) and environmental impacts (EcoX) has been developed. The higher the EcoX value, the higher is the overall environmental burden associated with the product under investigation. An environmental analysis of arable crop production systems based on this LCA method is especially appropriate in order to: (1) detect environmental hot spots in the system; (2) trace back environmental impacts of arable farming products to their sources and on that basis to suggest options for improvement; and (3) contribute to the debate on the environmental preference of alternative cropping systems in an informed way.

This study examined the environmental impact of different nitrogen (N) fertilizer rates in winter wheat production by using a new life cycle assessment (LCA) method, which was specifically tailored to crop production. The wheat production system studied was designed according to “good agricultural practice”. Information on crop yield response to different N rates was taken from a long-term field trial in the UK (Broadbalk Experiment, Rothamsted). The analysis considered the entire system, which was required to produce 1 ton of wheat grain. It included the extraction of raw materials (e.g. fossil fuels, minerals), the production and transportation of farming inputs (e.g. fertilizers) and all agricultural operations in the field (e.g. tillage, harvest). In a first step, all emissions and the consumption of resources connected to the different processes were listed in a Life Cycle Inventory (LCI) and related to a common unit, which is 1 ton of grain. Next a Life Cycle Impact Assessment (LCIA) was done, in which the inventory data are aggregated into indicators for environmental effects, which included resource depletion, land use, climate change, toxicity, acidification, and eutrophication. After normalization and weighting of the indicator values it was possible to calculate summarizing indicators for resource depletion and environmental impacts (EcoX). At N rates of 48, 96, 144 or 192 kg N/ha the environmental indicator “EcoX” showed similar values per ton of grain (0.16–0.22 EcoX/ton of grain). At N rates of zero, 240 and 288 kg N/ha the EcoX values were 100–232% higher compared with the lowest figure at an N rate of 96 kg N/ha. At very low N rates, ‘land use’ was the key- environmental-factor, whereas at high N rates ‘eutrophication’ was the major problem. The results revealed that agronomical optimal arable farming does not necessarily come into conflict with economic and environmental boundary conditions.

The suitability of the Life Cycle Assessment (LCA) methodology to analyse the environmental impact of agricultural production is investigated. The first part of an LCA is an inventory of all the resources used and emissions released due to the system under investigation. In the following step, i.e. the Life Cycle Impact Assessment the inventory data were analysed and aggregated in order to finally get one index representing the total environmental burden. For the Life Cycle Impact Assessment (LCIA) the Eco-indicator 95 method has been chosen, because this is a well-documented and regularly applied impact assessment method. The resulting index is called Eco-indicator value. The higher the Eco-indicator value the stronger is the total environmental impact of an analysed system. A sugar beet field experiment conducted in northeastern Germany was chosen as an example for the analysis. In this experiment three different nitrogen fertilisers (calcium ammonium nitrate=CAN, urea ammonium nitrate solution=UAN, urea) were used at optimum N rates. The obtained Eco-indicator values were clearly different for the N fertilisers used in the sugar beet trial. The highest value was observed for the system where urea was used as N source. The lowest Eco-indicator value has been calculated for the CAN system. The differences are mainly due to different ammonia volatilisation after application of the N fertilisers. For all the systems the environmental effects of acidification and eutrophication contributed most to the total Eco-indicator value. The results show that the LCA methodology is basically suitable to assess the environmental impact associated with agricultural production. A comparative analysis of the system, contribution to global warming, acidification, eutrophication and summer smog is possible. However, some important environmental issues are missing in the Eco-indicator 95 method (e.g. the use of resources and land).

This paper describes the successful grading of farmed eels using square meshed box screens. The grading curves for yellow and silver eels are evaluated for the square mesh sizes: 10, 16, 20 and 25 mm while some indication is given to the location of the sexes within these gradings.