Cell-line Engineering of Chinese Hamster Ovary Cells for Low-temperature Culture

Developments in mammalian cell culture and recombinant technology has allowed for the production of recombinant proteins for use as human therapeutics. Mammalian cell culture is typically operated at the physiological temperature of 37°. However, recent research has shown that the use of low-temperature conditions (30-33°) as a platform for cell-culture results in changes in cell characteristics, such as increased specific productivity and extended periods of cell viability, that can potentially improve the production of recombinant proteins. Furthermore, many recent reports have focused on investigating low-temperature mammalian cell culture of Chinese hamster ovary (CHO) cells, one of the principal cell-lines used in industrial production of recombinant proteins. Exposure to low ambient temperatures exerts an external stress on all living cells, and elicits a cellular response. This cold-stress response has been observed in bacteria, plants and mammals, and is regulated at the gene level. The exact genes and molecular mechanisms involved in the cold-stress response in prokaryotes and plants have been well studied. There are also various reports that detail the modification of cold-stress genes to improve the characteristics of bacteria or plant cells at low temperatures. However, there is very limited information on mammalian cold-stress genes or the related pathways governing the mammalian cold-stress response. This project seeks to investigate and characterise cold-stress genes that are differentially expressed during low-temperature culture of CHO cells, and to relate them to the various changes in cell characteristics observed in low-temperature culture of CHO cells. The gene information can then be used to modify CHO cell-lines for improved performance in the production of recombinant proteins.

EfeUOB (YcdNOB) is a tripartite, acid-induced and CpxAR-regulated, low-pH Fe2+ transporter that is cryptic in Escherichia coli K-12 but functional in E-coli O157 : H7

Escherichia coli possesses iron transporters specific for either Fe2+ or Fe3+. Although Fe2+ is far more soluble than Fe3+, it rapidly oxidizes aerobically at pH >= 7. Thus, FeoAB, the major Fe2+ transporter of E. coli, operates anaerobically. However, Fe2+ remains stable aerobically under acidic conditions, although a low-pH Fe2+ importer has not been previously identified. Here we show that ycdNOB (efeUOB) specifies the first such transporter. efeUOB is repressed at high pH by CpxAR, and is Fe2+-Fur repressed. EfeU is homologous to the high-affinity iron permease, Ftr1p, of Saccharomyces cerevisiae and other fungi. EfeO is periplasmic with a cupredoxin N-terminal domain; EfeB is also periplasmic and is haem peroxidase-like. All three Efe proteins are required for Efe function. The efeU gene of E. coli K-12 is cryptic due to a frameshift mutation - repair of the single-base-pair deletion generates a functional EfeUOB system. In contrast, the efeUOB operon of the enterohaemorrhagic strain, O157:1147, lacks any frameshift and is functional. A 'wild-type' K-12 strain bearing a functional EfeUOB displays a major growth advantage under aerobic, low-pH, low-iron conditions when a competing metal is provided. Fe-55 transport assays confirm the ferrous iron specificity of EfeUOB.

The role of sky conditions on gross primary production in a mixed deciduous forest

The role of different sky conditions on diffuse PAR fraction (ϕ), air temperature (Ta), vapor pressure deficit (vpd) and GPP in a deciduous forest is investigated using eddy covariance observations of CO2 fluxes and radiometer and ceilometer observations of sky and PAR conditions on hourly and growing season timescales. Maximum GPP response occurred under moderate to high PAR and ϕ and low vpd. Light response models using a rectangular hyperbola showed a positive linear relation between ϕ and effective quantum efficiency (α = 0.023ϕ + 0.012, r2 = 0.994). Since PAR and ϕ are negatively correlated, there is a tradeoff between the greater use efficiency of diffuse light and lower vpd and the associated decrease in total PAR available for photosynthesis. To a lesser extent, light response was also modified by vpd and Ta. The net effect of these and their relation with sky conditions helped enhance light response under sky conditions that produced higher ϕ. Six sky conditions were classified from cloud frequency and ϕ data: optically thick clouds, optically thin clouds, mixed sky (partial clouds within hour), high, medium and low optical aerosol. The frequency and light responses of each sky condition for the growing season were used to predict the role of changing sky conditions on annual GPP. The net effect of increasing frequency of thick clouds is to decrease GPP, changing low aerosol conditions has negligible effect. Increases in the other sky conditions all lead to gains in GPP. Sky conditions that enhance intermediate levels of ϕ, such as thin or scattered clouds or higher aerosol concentrations from volcanic eruptions or anthropogenic emissions, will have a positive outcome on annual GPP, while an increase in cloud cover will have a negative impact. Due to the ϕ/PAR tradeoff and since GPP response to changes in individual sky conditions differ in sign and magnitude, the net response of ecosystem GPP to future sky conditions is non-linear and tends toward moderation of change.

Variation in morphological and physiological parameters in herbaceous perennial legumes in response to phosphorus supply

Change in morphological and physiological parameters in response to phosphorus (P) supply was studied in 11 perennial herbaceous legume species, six Australian native (Lotus australis, Cullen australasicum, Kennedia prorepens, K. prostrata, Glycine canescens, C. tenax) and five exotic species (Medicago sativa, Lotononis bainesii, Bituminaria bituminosa var albomarginata, Lotus corniculatus, Macroptilium bracteatum). We aimed to identify mechanisms for P acquisition from soil. Plants were grown in sterilised washed river sand; eight levels of P as KH2PO4 ranging from 0 to 384 μg P g−1 soil were applied. Plant growth under low-P conditions strongly correlated with physiological P-use efficiency and/or P-uptake efficiency. Taking all species together, at 6 μg P g−1 soil there was a good correlation between P uptake and both root surface area and total root length. All species had higher amounts of carboxylates in the rhizosphere under a low level of P application. Six of the 11 species increased the fraction of rhizosphere citrate in response to low P, which was accompanied by a reduction in malonate, except L. corniculatus. In addition, species showed different plasticity in response to P-application levels and different strategies in response to P deficiency. Our results show that many of the 11 species have prospects for low-input agroecosystems based on their high P-uptake and P-use efficiency.

A comparison of global estimates of marine primary production from ocean color

The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

Multi-software modeling technique for field distribution propagation through an optical vertical interconnect assembly

Embedded siloxane polymer waveguides have shown promising results for use in optical backplanes. They exhibit high temperature stability, low optical absorption, and require common processing techniques. A challenging aspect of this technology is out-of-plane coupling of the waveguides. A multi-software approach to modeling an optical vertical interconnect (via) is proposed. This approach utilizes the beam propagation method to generate varied modal field distribution structures which are then propagated through a via model using the angular spectrum propagation technique. Simulation results show average losses between 2.5 and 4.5 dB for different initial input conditions. Certain configurations show losses of less than 3 dB and it is shown that in an input/output pair of vias, average losses per via may be lower than the targeted 3 dB.

Impact of different cultivation methods on the metabolic profile of apples studied by 1H HR-MAS NMR spectroscopy

The cultivation of dessert apples has to meet the consumer's increasing demand for high fruit quality and a sustainable mostly residue-free production while ensuring a competitive agricultural productivity. It is therefore of great interest to know the impact of different cultivation methods on the fruit quality and the chemical composition, respectively. Previous studies have demonstrated the feasibility of High Resolution Magic Angle Spinning (HR-MAS) NMR spectroscopy directly performed on apple tissue as analytical tool for metabonomic studies. In this study, HR-MAS NMR spectroscopy is applied to apple tissue to analyze the metabolic profiles of apples grown under 3 different cultivation methods. Golden Delicious apples were grown applying organic (Bio), integrated (IP) and low-input (LI) plant protection strategies. A total of 70 1H HR-MAS NMR spectra were analyzed by means of principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Apples derived from Bio-production could be well separated from the two other cultivation methods applying both, PCA and PLS-DA. Apples obtained from integrated (IP) and low-input (LI) production discriminated when taking the third PLS-component into account. The identified chemical composition and the compounds responsible for the separation, i.e. the PLS-loadings, are discussed. The results are compared with fruit quality parameters assessed by conventional methods. The present study demonstrates the potential of HR-MAS NMR spectroscopy of fruit tissue as analytical tool for finding markers for specific fruit production conditions like the cultivation method.

Experimental evidence for the immediate impact of fertilization and irrigation upon the plant and invertebrate communities of mountain grasslands

The response of montane and subalpine hay meadow plant and arthropod communities to the application of liquid manure and aerial irrigation – two novel, rapidly spreading management practices – remains poorly understood, which hampers the formulation of best practice management recommendations for both hay production and biodiversity preservation. In these nutrient-poor mountain grasslands, a moderate management regime could enhance overall conditions for biodiversity. This study experimentally assessed, at the site scale, among low-input montane and subalpine meadows, the short-term effects (1 year) of a moderate intensification (slurry fertilization: 26.7–53.3 kg N·ha−1·year−1; irrigation with sprinklers: 20 mm·week−1; singly or combined together) on plant species richness, vegetation structure, hay production, and arthropod abundance and biomass in the inner European Alps (Valais, SW Switzerland). Results show that (1) montane and subalpine hay meadow ecological communities respond very rapidly to an intensification of management practices; (2) on a short-term basis, a moderate intensification of very low-input hay meadows has positive effects on plant species richness, vegetation structure, hay production, and arthropod abundance and biomass; (3) vegetation structure is likely to be the key factor limiting arthropod abundance and biomass. Our ongoing experiments will in the longer term identify which level of management intensity achieves an optimal balance between biodiversity and hay production.

Molecular nitrogen in comet 67P/Churyumov-Gerasimenko indicates a low formation temperature

Molecular nitrogen (N2) is thought to have been the most abundant form of nitrogen in the protosolar nebula. It is the main N-bearing molecule in the atmospheres of Pluto and Triton and probably the main nitrogen reservoir from which the giant planets formed. Yet in comets, often considered the most primitive bodies in the solar system, N2 has not been detected. Here we report the direct in situ measurement of N2 in the Jupiter family comet 67P/Churyumov-Gerasimenko, made by the Rosetta Orbiter Spectrometer for Ion and Neutral Analysis mass spectrometer aboard the Rosetta spacecraft. A N2/CO ratio of Embedded Image (2σ standard deviation of the sampled mean) corresponds to depletion by a factor of ~25.4 ± 8.9 as compared to the protosolar value. This depletion suggests that cometary grains formed at low-temperature conditions below ~30 kelvin.

Benthic foraminiferal accumulation rates of the late Pliocene-Pleistocene in the northern Indian Ocean

During the late Pliocene-middle Pleistocene, 63 species of elongate, bathyal-upper abyssal benthic foraminifera (Extinction Group = Stilostomellidae, Pleurostomellidae, some Nodosariidae) declined in abundance and finally disappeared in the northern Indian Ocean (ODP Sites 722, 758), as part of the global extinction of at least 88 related species at this time. The detailed record of withdrawal of these species differs by depth and geography in the Indian Ocean. In northwest Indian Ocean Site 722 (2045 m), the Extinction Group of 54 species comprised 2-15% of the benthic foraminiferal fauna in the earliest Pleistocene, but declined dramatically during the onset of the mid-Pleistocene Transition (MPT) at 1.2-1.1 Ma, with all but three species disappearing by the end of the MPT (~0.6 Ma). In northeast Indian Ocean Site 758 (2925 m), the Extinction Group of 44 species comprised 1-5% of the benthic foraminiferal fauna at ~3.3-2.6 Ma, but declined in abundance and diversity in three steps, at ~2.5, 1.7, and 1.2 Ma, with all but one species disappearing by the end of the MPT. At both sites there are strong positive correlations between the accumulation rate of the Extinction Group and proxies indicating low-oxygen conditions with a high organic carbon input. In both sites, there was a pulsed decline in Extinction Group abundance and species richness, especially in glacial periods, with some partial recoveries in interglacials. We infer that the glacial declines at the deeper Site 758 were a result of increased production of colder, well-ventilated Antarctic Bottom Water (AABW), particularly in the late Pliocene and during the MPT. The Extinction Group at shallower water depths (Site 722) were not impacted by the deeper water mass changes until the onset of the MPT, when cold, well-ventilated Glacial North Atlantic Intermediate Water (GNAIW) production increased and may have spread into the Indian Ocean. Increased chemical ventilation at various water depths since late Pliocene, particularly in glacial periods, possibly in association with decreased or more fluctuating organic carbon flux, might be responsible for the pulsed global decline and extinction of this rather specialised group of benthic foraminifera.

Dolomite-rich coralline algae in reefs resist dissolution in acidified conditions

Coral reef ecosystems develop best in high-flow environments but their fragile frameworks are also vulnerable to high wave energy. Wave-resistant algal rims, predominantly made up of the crustose coralline algae (CCA) Porolithon onkodes and P. pachydermum, are therefore critical structural elements for the survival of many shallow coral reefs. Concerns are growing about the susceptibility of CCA to ocean acidification because CCA Mg-calcite skeletons are more susceptible to dissolution under low pH conditions than coral aragonite skeletons. However, the recent discovery of dolomite (Mg0.5Ca0.5(CO3)), a stable carbonate, in P. onkodes cells necessitates a reappraisal of the impacts of ocean acidification on these CCA. Here we show, using a dissolution experiment, that dried dolomite-rich CCA have 6-10 times lower rates of dissolution than predominantly Mg-calcite CCA in both high-CO2 (~ 700 ppm) and control (~ 380 ppm) environments, respectively. We reveal this stabilizing mechanism to be a combination of reduced porosity due to dolomite infilling and selective dissolution of other carbonate minerals. Physical break-up proceeds by dissolution of Mg-calcite walls until the dolomitized cell eventually drops out intact. Dolomite-rich CCA frameworks are common in shallow coral reefs globally and our results suggest that it is likely that they will continue to provide protection and stability for coral reef frameworks as CO2 rises.

Siliceous phytoplankton in Late Quaternary sediments of ODP Site 175-1077

Late Quaternary fluctuations in the intensity of Congo River freshwater load were reconstructed using three different proxies (marine and freshwater diatoms, and the delta18O record of Globigerinoides ruber) preserved in the sediments of Ocean Drilling Program (ODP) Site 1077, located at the northern rim of the Congo River fan (5°10'S, 10°26'E). An abrupt change in the diatom assemblage is evident at Termination II: a two- to four-fold increase in (a) the relative abundance of a marine planktonic diatom tolerant of low salinity conditions (Cyclotella litoralis), and (b) in the concentration of freshwater diatoms. The microfossil data suggest a change in the environmental conditions surrounding Site 1077 from predominantly marine to mixed marine/brackish/fresh. The delta18O record of the planktic foraminifera G. ruber (pink) revealed negative deviations from the global oxygen isotope signal since Termination II which occurred during warm stage 1 and substages 3.2, 5.1, 5.3, and 5.5. Comparison of the isotopic signal of ODP Site 1077 with the record from a pelagic location (core GeoB1041 at 3°48'S, 7°05'W) confirms these results. The construction of an artificial delta18O curve using alkenone-derived sea surface temperature (SST) data from a nearby core (GeoB1008 at 6°S, 10°E) allowed us to estimate salinity and temperature effects on the ODP Site 1077 isotopic signal. Although increased SSTs may account for lighter delta18O values during warmer periods, they do not explain the extremely light values documented in the sediments of Site 1077. We used the oxygen isotope difference (Delta delta18O) between our site and GeoB1041 as a proxy for freshwater input. A general trend in the Delta delta18O was observed, with more negative values since Termination II. In addition, conspicuous Delta delta18O negative pulses coincided with periods of northern hemisphere summer insolation maxima over the African continent, suggesting an increase in the freshwater discharge from the Congo River due to enhanced precipitation on the hinterland. Here we propose that the abrupt change in environmental conditions at Site 1077 since Termination II is a consequence of a major reorganization in the depositional environment of the Congo River delta. This reorganization involved sustained equatorward displacement of the Angola-Benguela Front causing a northward deflection of the Congo River plume thus moving plume waters further north than normal and over Site 1077.

An Intercomparison of Modelling Approaches for Simulating the Atmospheric Dispersion of Ammonia Emitted by Agricultural Sources

RESUMEN La dispersión del amoniaco (NH3) emitido por fuentes agrícolas en medias distancias, y su posterior deposición en el suelo y la vegetación, pueden llevar a la degradación de ecosistemas vulnerables y a la acidificación de los suelos. La deposición de NH3 suele ser mayor junto a la fuente emisora, por lo que los impactos negativos de dichas emisiones son generalmente mayores en esas zonas. Bajo la legislación comunitaria, varios estados miembros emplean modelos de dispersión inversa para estimar los impactos de las emisiones en las proximidades de las zonas naturales de especial conservación. Una revisión reciente de métodos para evaluar impactos de NH3 en distancias medias recomendaba la comparación de diferentes modelos para identificar diferencias importantes entre los métodos empleados por los distintos países de la UE. En base a esta recomendación, esta tesis doctoral compara y evalúa las predicciones de las concentraciones atmosféricas de NH3 de varios modelos bajo condiciones, tanto reales como hipotéticas, que plantean un potencial impacto sobre ecosistemas (incluidos aquellos bajo condiciones de clima Mediterráneo). En este sentido, se procedió además a la comparación y evaluación de varias técnicas de modelización inversa para inferir emisiones de NH3. Finalmente, se ha desarrollado un modelo matemático simple para calcular las concentraciones de NH3 y la velocidad de deposición de NH3 en ecosistemas vulnerables cercanos a una fuente emisora. La comparativa de modelos supuso la evaluación de cuatro modelos de dispersión (ADMS 4.1; AERMOD v07026; OPS-st v3.0.3 y LADD v2010) en un amplio rango de casos hipotéticos (dispersión de NH3 procedente de distintos tipos de fuentes agrícolas de emisión). La menor diferencia entre las concentraciones medias estimadas por los distintos modelos se obtuvo para escenarios simples. La convergencia entre las predicciones de los modelos fue mínima para el escenario relativo a la dispersión de NH3 procedente de un establo ventilado mecánicamente. En este caso, el modelo ADMS predijo concentraciones significativamente menores que los otros modelos. Una explicación de estas diferencias podríamos encontrarla en la interacción de diferentes “penachos” y “capas límite” durante el proceso de parametrización. Los cuatro modelos de dispersión fueron empleados para dos casos reales de dispersión de NH3: una granja de cerdos en Falster (Dinamarca) y otra en Carolina del Norte (EEUU). Las concentraciones medias anuales estimadas por los modelos fueron similares para el caso americano (emisión de granjas ventiladas de forma natural y balsa de purines). La comparación de las predicciones de los modelos con concentraciones medias anuales medidas in situ, así como la aplicación de los criterios establecidos para la aceptación estadística de los modelos, permitió concluir que los cuatro modelos se comportaron aceptablemente para este escenario. No ocurrió lo mismo en el caso danés (nave ventilada mecánicamente), en donde el modelo LADD no dio buenos resultados debido a la ausencia de procesos de “sobreelevacion de penacho” (plume-rise). Los modelos de dispersión dan a menudo pobres resultados en condiciones de baja velocidad de viento debido a que la teoría de dispersión en la que se basan no es aplicable en estas condiciones. En situaciones de frecuente descenso en la velocidad del viento, la actual guía de modelización propone usar un modelo que sea eficaz bajo dichas condiciones, máxime cuando se realice una valoración que tenga como objeto establecer una política de regularización. Esto puede no ser siempre posible debido a datos meteorológicos insuficientes, en cuyo caso la única opción sería utilizar un modelo más común, como la versión avanzada de los modelos Gausianos ADMS o AERMOD. Con el objetivo de evaluar la idoneidad de estos modelos para condiciones de bajas velocidades de viento, ambos modelos fueron utilizados en un caso con condiciones Mediterráneas. Lo que supone sucesivos periodos de baja velocidad del viento. El estudio se centró en la dispersión de NH3 procedente de una granja de cerdos en Segovia (España central). Para ello la concentración de NH3 media mensual fue medida en 21 localizaciones en torno a la granja. Se realizaron también medidas de concentración de alta resolución en una única localización durante una campaña de una semana. En este caso, se evaluaron dos estrategias para mejorar la respuesta del modelo ante bajas velocidades del viento. La primera se basó en “no zero wind” (NZW), que sustituyó periodos de calma con el mínimo límite de velocidad del viento y “accumulated calm emissions” (ACE), que forzaban al modelo a calcular las emisiones totales en un periodo de calma y la siguiente hora de no-calma. Debido a las importantes incertidumbres en los datos de entrada del modelo (inputs) (tasa de emisión de NH3, velocidad de salida de la fuente, parámetros de la capa límite, etc.), se utilizó el mismo caso para evaluar la incertidumbre en la predicción del modelo y valorar como dicha incertidumbre puede ser considerada en evaluaciones del modelo. Un modelo dinámico de emisión, modificado para el caso de clima Mediterráneo, fue empleado para estimar la variabilidad temporal en las emisiones de NH3. Así mismo, se realizó una comparativa utilizando las emisiones dinámicas y la tasa constante de emisión. La incertidumbre predicha asociada a la incertidumbre de los inputs fue de 67-98% del valor medio para el modelo ADMS y entre 53-83% del valor medio para AERMOD. La mayoría de esta incertidumbre se debió a la incertidumbre del ratio de emisión en la fuente (50%), seguida por la de las condiciones meteorológicas (10-20%) y aquella asociada a las velocidades de salida (5-10%). El modelo AERMOD predijo mayores concentraciones que ADMS y existieron más simulaciones que alcanzaron los criterios de aceptabilidad cuando se compararon las predicciones con las concentraciones medias anuales medidas. Sin embargo, las predicciones del modelo ADMS se correlacionaron espacialmente mejor con las mediciones. El uso de valores dinámicos de emisión estimados mejoró el comportamiento de ADMS, haciendo empeorar el de AERMOD. La aplicación de estrategias destinadas a mejorar el comportamiento de este último tuvo efectos contradictorios similares. Con el objeto de comparar distintas técnicas de modelización inversa, varios modelos (ADMS, LADD y WindTrax) fueron empleados para un caso no agrícola, una colonia de pingüinos en la Antártida. Este caso fue empleado para el estudio debido a que suponía la oportunidad de obtener el primer factor de emisión experimental para una colonia de pingüinos antárticos. Además las condiciones eran propicias desde el punto de vista de la casi total ausencia de concentraciones ambiente (background). Tras el trabajo de modelización existió una concordancia suficiente entre las estimaciones obtenidas por los tres modelos. De este modo se pudo definir un factor de emisión de para la colonia de 1.23 g NH3 por pareja criadora por día (con un rango de incertidumbre de 0.8-2.54 g NH3 por pareja criadora por día). Posteriores aplicaciones de técnicas de modelización inversa para casos agrícolas mostraron también un buen compromiso estadístico entre las emisiones estimadas por los distintos modelos. Con todo ello, es posible concluir que la modelización inversa es una técnica robusta para estimar tasas de emisión de NH3. Modelos de selección (screening) permiten obtener una rápida y aproximada estimación de los impactos medioambientales, siendo una herramienta útil para evaluaciones de impactos en tanto que permite eliminar casos que presentan un riesgo potencial de daño bajo. De esta forma, lo recursos del modelo pueden Resumen (Castellano) destinarse a casos en donde la posibilidad de daño es mayor. El modelo de Cálculo Simple de los Límites de Impacto de Amoniaco (SCAIL) se desarrolló para obtener una estimación de la concentración media de NH3 y de la tasa de deposición seca asociadas a una fuente agrícola. Está técnica de selección, basada en el modelo LADD, fue evaluada y calibrada con diferentes bases de datos y, finalmente, validada utilizando medidas independientes de concentraciones realizadas cerca de las fuentes. En general SCAIL dio buenos resultados de acuerdo a los criterios estadísticos establecidos. Este trabajo ha permitido definir situaciones en las que las concentraciones predichas por modelos de dispersión son similares, frente a otras en las que las predicciones difieren notablemente entre modelos. Algunos modelos nos están diseñados para simular determinados escenarios en tanto que no incluyen procesos relevantes o están más allá de los límites de su aplicabilidad. Un ejemplo es el modelo LADD que no es aplicable en fuentes con velocidad de salida significativa debido a que no incluye una parametrización de sobreelevacion del penacho. La evaluación de un esquema simple combinando la sobreelevacion del penacho y una turbulencia aumentada en la fuente mejoró el comportamiento del modelo. Sin embargo más pruebas son necesarias para avanzar en este sentido. Incluso modelos que son aplicables y que incluyen los procesos relevantes no siempre dan similares predicciones. Siendo las razones de esto aún desconocidas. Por ejemplo, AERMOD predice mayores concentraciones que ADMS para dispersión de NH3 procedente de naves de ganado ventiladas mecánicamente. Existe evidencia que sugiere que el modelo ADMS infraestima concentraciones en estas situaciones debido a un elevado límite de velocidad de viento. Por el contrario, existen evidencias de que AERMOD sobreestima concentraciones debido a sobreestimaciones a bajas Resumen (Castellano) velocidades de viento. Sin embrago, una modificación simple del pre-procesador meteorológico parece mejorar notablemente el comportamiento del modelo. Es de gran importancia que estas diferencias entre las predicciones de los modelos sean consideradas en los procesos de evaluación regulada por los organismos competentes. Esto puede ser realizado mediante la aplicación del modelo más útil para cada caso o, mejor aún, mediante modelos múltiples o híbridos. ABSTRACT Short-range atmospheric dispersion of ammonia (NH3) emitted by agricultural sources and its subsequent deposition to soil and vegetation can lead to the degradation of sensitive ecosystems and acidification of the soil. Atmospheric concentrations and dry deposition rates of NH3 are generally highest near the emission source and so environmental impacts to sensitive ecosystems are often largest at these locations. Under European legislation, several member states use short-range atmospheric dispersion models to estimate the impact of ammonia emissions on nearby designated nature conservation sites. A recent review of assessment methods for short-range impacts of NH3 recommended an intercomparison of the different models to identify whether there are notable differences to the assessment approaches used in different European countries. Based on this recommendation, this thesis compares and evaluates the atmospheric concentration predictions of several models used in these impact assessments for various real and hypothetical scenarios, including Mediterranean meteorological conditions. In addition, various inverse dispersion modelling techniques for the estimation of NH3 emissions rates are also compared and evaluated and a simple screening model to calculate the NH3 concentration and dry deposition rate at a sensitive ecosystem located close to an NH3 source was developed. The model intercomparison evaluated four atmospheric dispersion models (ADMS 4.1; AERMOD v07026; OPS-st v3.0.3 and LADD v2010) for a range of hypothetical case studies representing the atmospheric dispersion from several agricultural NH3 source types. The best agreement between the mean annual concentration predictions of the models was found for simple scenarios with area and volume sources. The agreement between the predictions of the models was worst for the scenario representing the dispersion from a mechanically ventilated livestock house, for which ADMS predicted significantly smaller concentrations than the other models. The reason for these differences appears to be due to the interaction of different plume-rise and boundary layer parameterisations. All four dispersion models were applied to two real case studies of dispersion of NH3 from pig farms in Falster (Denmark) and North Carolina (USA). The mean annual concentration predictions of the models were similar for the USA case study (emissions from naturally ventilated pig houses and a slurry lagoon). The comparison of model predictions with mean annual measured concentrations and the application of established statistical model acceptability criteria concluded that all four models performed acceptably for this case study. This was not the case for the Danish case study (mechanically ventilated pig house) for which the LADD model did not perform acceptably due to the lack of plume-rise processes in the model. Regulatory dispersion models often perform poorly in low wind speed conditions due to the model dispersion theory being inapplicable at low wind speeds. For situations with frequent low wind speed periods, current modelling guidance for regulatory assessments is to use a model that can handle these conditions in an acceptable way. This may not always be possible due to insufficient meteorological data and so the only option may be to carry out the assessment using a more common regulatory model, such as the advanced Gaussian models ADMS or AERMOD. In order to assess the suitability of these models for low wind conditions, they were applied to a Mediterranean case study that included many periods of low wind speed. The case study was the dispersion of NH3 emitted by a pig farm in Segovia, Central Spain, for which mean monthly atmospheric NH3 concentration measurements were made at 21 locations surrounding the farm as well as high-temporal-resolution concentration measurements at one location during a one-week campaign. Two strategies to improve the model performance for low wind speed conditions were tested. These were ‘no zero wind’ (NZW), which replaced calm periods with the minimum threshold wind speed of the model and ‘accumulated calm emissions’ (ACE), which forced the model to emit the total emissions during a calm period during the first subsequent non-calm hour. Due to large uncertainties in the model input data (NH3 emission rates, source exit velocities, boundary layer parameters), the case study was also used to assess model prediction uncertainty and assess how this uncertainty can be taken into account in model evaluations. A dynamic emission model modified for the Mediterranean climate was used to estimate the temporal variability in NH3 emission rates and a comparison was made between the simulations using the dynamic emissions and a constant emission rate. Prediction uncertainty due to model input uncertainty was 67-98% of the mean value for ADMS and between 53-83% of the mean value for AERMOD. Most of this uncertainty was due to source emission rate uncertainty (~50%), followed by uncertainty in the meteorological conditions (~10-20%) and uncertainty in exit velocities (~5-10%). AERMOD predicted higher concentrations than ADMS and more of the simulations met the model acceptability criteria when compared with the annual mean measured concentrations. However, the ADMS predictions were better correlated spatially with the measurements. The use of dynamic emission estimates improved the performance of ADMS but worsened the performance of AERMOD and the application of strategies to improved model performance had similar contradictory effects. In order to compare different inverse modelling techniques, several models (ADMS, LADD and WindTrax) were applied to a non-agricultural case study of a penguin colony in Antarctica. This case study was used since it gave the opportunity to provide the first experimentally-derived emission factor for an Antarctic penguin colony and also had the advantage of negligible background concentrations. There was sufficient agreement between the emission estimates obtained from the three models to define an emission factor for the penguin colony (1.23 g NH3 per breeding pair per day with an uncertainty range of 0.8-2.54 g NH3 per breeding pair per day). This emission estimate compared favourably to the value obtained using a simple micrometeorological technique (aerodynamic gradient) of 0.98 g ammonia per breeding pair per day (95% confidence interval: 0.2-2.4 g ammonia per breeding pair per day). Further application of the inverse modelling techniques for a range of agricultural case studies also demonstrated good agreement between the emission estimates. It is concluded, therefore, that inverse dispersion modelling is a robust technique for estimating NH3 emission rates. Screening models that can provide a quick and approximate estimate of environmental impacts are a useful tool for impact assessments because they can be used to filter out cases that potentially have a minimal environmental impact allowing resources to be focussed on more potentially damaging cases. The Simple Calculation of Ammonia Impact Limits (SCAIL) model was developed as a screening model to provide an estimate of the mean NH3 concentration and dry deposition rate downwind of an agricultural source. This screening tool, based on the LADD model, was evaluated and calibrated with several experimental datasets and then validated using independent concentration measurements made near sources. Overall SCAIL performed acceptably according to established statistical criteria. This work has identified situations where the concentration predictions of dispersion models are similar and other situations where the predictions are significantly different. Some models are simply not designed to simulate certain scenarios since they do not include the relevant processes or are beyond the limits of their applicability. An example is the LADD model that is not applicable to sources with significant exit velocity since the model does not include a plume-rise parameterisation. The testing of a simple scheme combining a momentum-driven plume rise and increased turbulence at the source improved model performance, but more testing is required. Even models that are applicable and include the relevant process do not always give similar predictions and the reasons for this need to be investigated. AERMOD for example predicts higher concentrations than ADMS for dispersion from mechanically ventilated livestock housing. There is evidence to suggest that ADMS underestimates concentrations in these situations due to a high wind speed threshold. Conversely, there is also evidence that AERMOD overestimates concentrations in these situations due to overestimation at low wind speeds. However, a simple modification to the meteorological pre-processor appears to improve the performance of the model. It is important that these differences between the predictions of these models are taken into account in regulatory assessments. This can be done by applying the most suitable model for the assessment in question or, better still, using multiple or hybrid models.

Evolution not revolution of farming systemswill best feed and green the world

The challenge to properly feed a world population of 9.2 billion by 2050, that must be achieved on essentially currently cropped area, requires that food production be increased by 70%. This large increase can only be achieved by combinations of greater crop yields and more intensive cropping adapted to local conditions and availability of inputs. Farming systems are dynamic and continuously adapt to changing ecological, environmental and social conditions, while achieving greater production and resource-use efficiency by application of science and technology. This article argues that the solution to feed and green the world in 2050 is to support this evolution more strongly by providing farmers with necessary information, inputs, and recognition. There is no revolutionary alternative. Proposals to transform agriculture to low-input and organic systems would, because of low productiv- ity, exacerbate the challenge if applied in small part, and ensure failure if applied more widely. The challenge is, however, great. Irrigation, necessary to increase cropping intensity in many areas cannot be extended much more widely than at present, and it is uncertain if the current rate of crop yield increase can be maintained. Society needs greater recognition of the food-supply problem and must increase funding and support for agricultural research while it attends to issues of food waste and over consumption that can make valuable reductions to food demand from agriculture