Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

Optimizing rabbit production under heat stress: cage density and cage size during fattening, and breeding system and water quality on rabbit does

The aim of this work was to evaluate different management strategies to optimize rabbit production under chronic heat stress. To achieve it, three trials were conducted. In the first trial, to find the optimal cage density in tropical very dry forest condition, were measured growth performance, mortality rate, injured animals and carcass performance over an initial population of 300 cross-breed rabbits of New Zealand, California, Butterfly, Dutch and Satin, weaned at 30 days (535 ± 8 g, standard error). Treatments evaluated were: 6, 12, 18 and 24 rabbits/m2 (3, 6, 9 and 12 rabbits/cage, respectively, each cage of 0.5 m2). The maximal temperature-humidity index indicated a severe heat stress from weaning to 2.2 kg body weight (experimental time). At the end of experimental period 10, 20, 30 and 30 rabbits from the treatments of 6, 12, 18 and 24 rabbits/m2, respectively, were slaughtered and carcass performance recorded. Average daily gain and feed intake decreased by 0.31 ± 0.070 and 1.20 ± 0.25 g, respectively, per each unit that the density increased at the beginning of the experiment (P = 0.001). It increased the length of the fattening period by 0.91 ± 0.16 d (P = 0.001) per each unit of increment of density. However, rabbit production (kg/m2) increased linear and quadratically with the density (P < 0.008). Animals housed at the highest density compared to the lower one tended to show a higher incidence of ringworm (68.9 vs 39.4%; P = 0.075), injured animals (16.8 vs 3.03%; P = 0.12) and mortality (20.5 vs 9.63%; P = 0.043). The proportion of scapular fat (P = 0.042) increased linearly with increasing levels of density. Increasing density reduced linearly dorsal length (P = 0.001), and reduced linear and quadratically drip loss percentage (P = 0.097 and 0.018, respectively). In the second trial, 46 nulliparous rabbit does (23 clipped and 23 unclipped) with a BW of 3.67 ± 0.05 kg (s.e.) were used to evaluate heat stress and circadian rhythms comparing unclipped and clipped rabbit does, and to study if a more extensive breeding system increase litters performance at weaning without impairing rabbit doe performance,. Rectal temperature, feed and water 4 intake were recorded for 24 h. Rabbit does were mated 7 d after circadian measurements, and randomly assigned to two breeding systems. Control (C): mated at 14 d after parturition + litter weaned at 35 d of age. Extensive (E): mate at 21 after parturition + litter weaned at 42 d of age. The first three cycles were evaluated concerning to rabbit doe and litter performance. Two hundred twenty eight weaned rabbits, were divided into two cage sizes: 0.5 and 0.25 m2 with same density (16 rabbit/m2) and growing performance was recorded. Farm and rectal temperatures were minimal and feed and water intake maximal during the night (P < 0.001). Unclipped rabbit does showed higher rectal temperature (P = 0.045) and lower feed intake respect to clipped does (P = 0.019) which suggest a lower heat stress in the latter. Kits weaned per litter was reduced by 33% (P=0.038) in C group. This reduction was more important in the 2nd and 3rd cycles compared to the first (P ≤ 0.054). Rabbit doe feed efficiency tended to decrease in E respect C group (P = 0.093), whereas it was impaired from the first to the third cycle by 48% (P = 0.014). Growing rabbits from the E group were heavier at weaning (by 38%. P < 0.001), showed a higher feed intake (+7.4%) and lower feed efficiency (-8.4%) throughout the fattening period (P ≤ 0.056) respect to C group. Cage size had minor influence in growing performance. In the third trial, forty five non pregnant and non lactating rabbit does (21 nulliparous and 24 multiparous) were assigned randomly to farm water and to potable water to study if a water quality improvement can affect positively rabbit doe response to heat stress during pregnancy and lactation. A transponder was implanted in each animal to record subcutaneous temperature at 07:30 and 14:30 h. Experimental period extended from pregnancy (with no lactation) to the next lactation (until day 28). Body temperature and milk production were recorded daily, and body condition, feed and water intake weekly. Water quality did not affect any trait (P ≥ 0.15). Pregnant rabbit does were classified as does that weaned (W: 47%), not weaned (NW: 44%) or those pregnant that did not deliver (NB: 9%). Body temperature and feed intake decreased during pregnancy (P ≤ 0.031), but water intake remained constant. In this period body temperature decreased with metabolic weight (P ≤ 0.009). In W and NW does, 5 from mating to birth energy and protein balance impaired (P≤0.011). Body temperature of W does tended to be the lowest (P ≤ 0.090). Pregnancy length and total number of kits born tended to be longer and higher in NW than in W does (P = 0.10 and 0.053, respectively). Kit mortality at birth and from birth to 14 d of lactation was high, being worse for NW than for W does (97 vs. 40%; P<0.001). Body temperature during lactation was maximal at day 12, and milk production increased it (P ≤ 0.025). . In conclusion, in our heat stress conditions densities higher than 18 rabbits/m2 (34 kg/m2) at the end of fattening, are not recommended despite cage size, gestation and lactation productivity impaired not only when lactation is extended and along successive reproductive cycles but also due to a reduced embryo/kit survival and finally water quality improvement did not attenuate negative effect of heat stress. RESUMEN El propósito de éste trabajo fue evaluar diferentes estrategias de manejo para optimizar la producción de conejos bajo estrés térmico. Para lo cual se desarrollaron tres experimentos. En el primer experimento, para encontrar el número óptimo de gazapos por m2 de jaula durante el cebo en condiciones de bosque muy seco tropical, se estudiaron los rendimientos durante el cebo, mortalidad, animales lesionados y rendimiento de la canal sobre una población inicial de 300 conejos mestizos de Nueva Zelanda, California, Mariposa, Holandés y Satin, destetados a los 30 días de edad (535 ± 8g, error estándar). Los tratamientos evaluados fueron: 6, 12, 18 y 24 conejos/m2 (3, 6, 9 y 12 conejos/jaula, respectivamente, en jaulas de 0.5 m2). Durante el período experimental (destete a 2.2 kg de peso vivo), se observaron valores de THI correspondientes con un estrés térmico severo (THI max. De 31 a 35). Al final del período experimental, 10, 20, 30, y 30 conejos de los tratamientos con densidades de 6, 12, 18 y 24 conejos/m2, respectivamente, fueron sacrificados y su canal fue valorada. El promedio de la ganancia diaria y el consumo de alimento disminuyeron en 0.31 ± 0.070 y 1.20 ± 0.25 g, respectivamente, por cada unidad de incremento en la densidad al inicio del experimento (P=0.001). Esto alargó el período de engorde en 0.91 ± 0.16 d (P=0.001) por cada unidad de incremento de la densidad. Sin embargo, la producción de conejos (kg/m2) aumentó lineal y cuadráticamente con la densidad (P<0.008). Los animales alojados en las mayores densidades en comparación con el resto tendieron a mostrar una mayore incidencia de tiña (68.9 vs 39.4%; P=0.075), de cantidad de animales heridos (16.8 vs 3.03%; P=0.12), así como de mortalidad (20.5 vs 9.63%; P=0.043). El aumento en la densidad aumentó linealmente la proporción de grasa escapular (P=0.042) y redujo linealmente la longitud dorsal (P=0.001), y lineal y cuadráticamente el porcentaje de pérdida por goteo (P=0.018). En el segundo experimento, 46 conejas nulliparas (23 rasuradas y 23 no rasuradas) con un peso vivo de 3.67 ± 0.05 kg (e.e.) fueron usadas para evaluar el estrés 8 térmico y los ritmos circadianos comparando conejas rasuradas o no, y estudiar si un sistema de crianza más extensivo mejora el desempeño de la camada al destete sin perjudicar la productividad de la coneja. Durante 24 h se midió la temperatura rectal, consumo de alimento y de agua. Las conejas fueron montadas 7 días después, y distribuidas en dos sistemas de crianza. El control (C): monta a 14 días posparto y destete a 35 d de edad. El extensivo (E): monta a 21 días posparto y destete a 42 d de edad. Se controló la productividad de la coneja y la camada durante los tres primeros ciclos. Doscientos veintiocho gazapos fueron distribuidos en dos tamaños de jaulas (0.5 y 0.25 m2) con la misma densidad (16 conejos/m2) y se controlaron sus rendimientos productivos. Durante la noche se observaron los valores mínimos para la temperatura ambiental y rectal, y los máximos para consumo de alimento y agua (P< 0.001). Las conejas no rasuradas mostraron mayor temperatura rectal (P=0.045) y menores valores de consumo de alimento con respecto a las conejas rasuradas (P=0.019), lo que sugiere un menor estrés térmico en las últimas. El número de gazapos destetados por camada se redujo en 33% (P=0.038) en el grupo C. Este comportamiento se acentuó en el 2do y 3er ciclo en comparación con el primero (P≤0.054). La eficiencia alimenticia de las conejas tendió a disminuir en el grupo E con respecto al grupo C (P=0.093), dicha tendencia se acentúa del primer al tercer ciclo en un 48% (P=0.014). Los gazapos en fase de crecimiento provenientes del grupo E fueron más pesados al momento del destete (en 38% P<0.001), mostrando un mayor consumo de alimento (+7.4%) y menor eficiencia alimenticia (-8.4%) a lo largo del engorde (P≤0.056) con respecto al grupo C. El tamaño de la jaula tuvo una mínima influencia en el comportamiento durante el crecimiento de éstos gazapos. En el tercer experimento, cuarenta y cinco conejas no gestantes ni lactantes (21 nulíparas y 24 multíparas) se les asignó al azar agua dos tipos de agua: común de la granja y agua potable, con el fin de estudiar si una mejora en la calidad del agua puede afectar positivamente la respuesta de la coneja al estrés térmico durante la gestación y la lactancia. Se les implantó un transponder para registrar la temperatura subcutánea a las 7:30 y a las 14:30 h. El período experimental se extendió desde la gestación (sin 9 lactancia) hasta la lactanción consecutiva (hasta los 28 días). La temperatura corporal y la producción de leche se controlaron diariamente, y la condición corporal, consumo de agua y alimento, semanalmente. La calidad del agua no afectó a ninguna variable (P≥0.15). Las conejas preñadas fueron clasificadas como conejas que destetaron (W: 47%), que no destetaron (NW:44%) o aquellas que no parieron (NB: 9%). La temperatura corporal y consumo de alimento disminuyeron durante la gestación (P≤0.031), mientras que el consumo de agua se mantuvo constante. La temperatura corporal descendió con el peso metabólico durante la gestación (P≤0.009). El balance de energía y proteína disminuyó desde la monta al parto para las conejas W y NW (P≤0.011). Durante la gestación la temperatura corporal tendió a ser menor en las conejas W (P≤0.090). La longitud de la gestación y el número total de gazapos nacidos tendieron a ser mayores en conejas NW que en conejas W (P=0.10 y 0.053, respectivamente). La mortalidad de los gazapos al parto y del parto a los 14 días de lactancia fue alta, siendo peor para las conejas NW que para las W (97 vs 40%; P<0.001). Durante la lactancia la temperatura corporal alcanzó su valor máximo para el día 12, y la producción de leche indujo un incremento en la misma (P≤0.025). En conclusión, en nuestras condiciones de estrés térmico y sin importar el tamaño de la jaula, no se recomiendan densidades mayores a 18 conejos/m2 (34 kg/m2) al final del engorde. La productividad de la gestación y la lactancia disminuyen cuando la lactancia es mayor y se suceden varios ciclos reproductivos seguidos. Esto se debe al efecto negativo del estrés térmico sobre la vitalidad y supervivencia del embrión/gazapo. La mejora de la calidad del agua atenuó el efecto negativo del estrés térmico. Las conejas más productoras parece que son aquéllas que consiguen manejar mejor el estrés térmico.

Farm nitrogen balances in six European landscapes as an indicator for nitrogen losses and basis for improved management.

Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

Managing Soil Organic Carbon: A Farm Perspective

Farming practices that lead to declining returns and inputs of carbon to soils pose a threat to key soil functions. The EU FP 7 interdisciplinary project Smart SOIL is using scientific testing and modeling to identify management practices that can optimize soil carbon storage and crop productivity. A consultation with advisors and policymakers in six European case study regions seeks to identify barriers to, and incentives for, uptake of such practices. Results from preliminary interviews are reported. Overall advisor and farmer awareness of management practices specifically directed towards soil carbon. is low. Most production- related decisions are taken in the short term, but managing soil carbon needs a long- term approach. Key barriers to uptake of practices include: perceived scientifi c uncertainty about the effi cacy of practices; lack of real life ?best practice? examples to show farmers; diffi culty in demonstrating the positive effects of soil carbon management practices and economic benefi ts over a long time scale; and advisors being unable to provide suitable advice due to inadequate information or training. Most farmers are unconvinced of the economic benefi ts of practices for managing soil carbon. Incentives are therefore needed, either as subsidies or as evidence of the cost effectiveness of practices. All new measures and advice should be integrated into existing programmes to avoid a fragmented policy approach.

Can small horticulture crops improve family farm incomes in mountains areas of Central America?

Small family farm in mountain areas can found in horticulture one alternative to increase incomes. Horticulture crop required more labour and increased the land intensification. Market of production will be the key factor in the future of this family farms.