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- ItemAmmonia 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, AndrewStorage 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.
- ItemAssessing the organic fraction of municipal solid wastes for the production of lactic acid(Amsterdam [u.a.] : Elsevier, 2019) López-Gómez, J. Pablo; Latorre-Sánchez, Marcos; Unger, Peter; Schneider, Roland; Coll Lozano, Caterina; Venus, JoachimWith an estimated yearly production of about 140 Mt in the EU, conventionally, the organic fraction of municipal solid wastes (OFMSW) has been disposed in landfills with negative environmental effects. Nonetheless, the chemical composition of this residue make it a substrate with great bioconversion potential. In this study, OFMSW from Spanish municipal treatment plants, were evaluated for the production of LA. Samples were identified according to the sorting mechanisms employed for their collection in: (A) separately collected, (B) non-separately collected and (C) separately collected+paper/cardboard. Enzymatic hydrolysis was used to produce hydrolysates A, B and C accordingly. Hydrolysate A showed the highest total sugars and glucose content with values of 70 and 55 g·L−1, respectively. Following the characterisation, a screening showed that growth of B. coagulans was possible in all three hydrolysates. Furthermore, lab scale fermentations showed that LA final concentrations could reach around 60 g·L−1, with yields from total sugars of above 0.60 g·g−1. A technical scale fermentation of the hydrolysate A resulted in a final LA concentration of 60.7 g·L−1, a yield of 0.71 g·g−1 with a productivity of 2.68 g·L−1·h−1. Overall, it was estimated that 0.23 g of LA could be produced from one g of dry OFMSW.
- ItemLaser induced diffuse reflectance imaging – Monte Carlo simulation of backscattering measured on the surface(Amsterdam [u.a.] : Elsevier, 2020) Baranyai, LászlóThe Monte Carlo simulation algorithm of photon trajectory computation is implemented in object oriented R code. Diffuse reflectance, also called backscattering, is modeled in semi-infinite homogeneous media. Spatial photon flux leaving the surface of the media is collected. The profile of intensity along radii relative to the incident point is used to simulate measurement of computer vision systems. Four optical parameters of the media are used: absorption coefficient, scattering coefficient, anisotropy factor and refractive index. Five parameters are used to describe configuration of the vision system: number of photons, radius of circular light beam, limiting energy level of photons, radius of observed area, spatial resolution of the vision system. • The incident angle of the light beam is included in the photon launch procedure. Initial direction is typically assumed to be normal with x,y,z coordinates of 0,0,1. In the proposed modification, initial move vector is calculated based on the incident angle and refractive index of the media. Additionally, elliptic distortion of the circular light beam on the surface is calculated based on the incident angle. • Photon flux leaving media through the surface is corrected with Lambertian method to measure intensity captured by an imaging device in normal position. • The software implementing the method is written in R language, the R code is available as standard package.
- ItemMeasures 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, BarbaraInputs 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
- ItemPrediction 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, BerndThis 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.
- ItemDynamics of rural livelihoods and rainfall variability in Northern Ethiopian Highlands(Amsterdam [u.a.] : Elsevier, 2019) Adamseged, Muluken E.; Frija, Aymen; Thiel, Andreas[No abstract available]