Simple training tool is insufficient for appropriate diagnosis and treatment of malnutrition: A pre-post intervention study in a tertiary center.

OBJECTIVES To improve malnutrition awareness and management in our department of general internal medicine; to assess patients' nutritional risk; and to evaluate whether an online educational program leads to an increase in basic knowledge and more frequent nutritional therapies. METHODS A prospective pre-post intervention study at a university department of general internal medicine was conducted. Nutritional screening using Nutritional Risk Score 2002 (NRS 2002) was performed, and prescriptions of nutritional therapies were assessed. The intervention included an online learning program and a pocket card for all residents, who had to fill in a multiple-choice questions (MCQ) test about basic nutritional knowledge before and after the intervention. RESULTS A total of 342 patients were included in the preintervention phase, and 300 were in the postintervention phase. In the preintervention phase, 54.1% were at nutritional risk (NRS 2002 ≥3) compared with 61.7% in the postintervention phase. There was no increase in the prescription of nutritional therapies (18.7% versus 17.0%). Forty-nine and 41 residents (response rate 58% and 48%) filled in the MCQ test before and after the intervention, respectively. The mean percentage of correct answers was 55.6% and 59.43%, respectively (which was not significant). Fifty of 84 residents completed the online program. The residents who participated in the whole program scored higher on the second MCQ test (63% versus 55% correct answers, P = 0.031). CONCLUSIONS Despite a high ratio of malnourished patients, the nutritional intervention, as assessed by nutritional prescriptions, is insufficient. However, the simple educational program via Internet and usage of NRS 2002 pocket cards did not improve either malnutrition awareness or nutritional treatment. More sophisticated educational systems to fight malnutrition are necessary.

SOMS: SurrOgate MultiStart algorithm for use with nonlinear programming for global optimization

SOMS is a general surrogate-based multistart algorithm, which is used in combination with any local optimizer to find global optima for computationally expensive functions with multiple local minima. SOMS differs from previous multistart methods in that a surrogate approximation is used by the multistart algorithm to help reduce the number of function evaluations necessary to identify the most promising points from which to start each nonlinear programming local search. SOMS’s numerical results are compared with four well-known methods, namely, Multi-Level Single Linkage (MLSL), MATLAB’s MultiStart, MATLAB’s GlobalSearch, and GLOBAL. In addition, we propose a class of wavy test functions that mimic the wavy nature of objective functions arising in many black-box simulations. Extensive comparisons of algorithms on the wavy testfunctions and on earlier standard global-optimization test functions are done for a total of 19 different test problems. The numerical results indicate that SOMS performs favorably in comparison to alternative methods and does especially well on wavy functions when the number of function evaluations allowed is limited.

Genome-wide algorithm for detecting CNV associations with diseases

SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). The quality of the inferences about copy number can be affected by many factors including batch effects, DNA sample preparation, signal processing, and analytical approach. Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP genotyping data. However, these algorithms lack specificity to detect small CNVs due to the high false positive rate when calling CNVs based on the intensity values. Association tests based on detected CNVs therefore lack power even if the CNVs affecting disease risk are common. In this research, by combining an existing Hidden Markov Model (HMM) and the logistic regression model, a new genome-wide logistic regression algorithm was developed to detect CNV associations with diseases. We showed that the new algorithm is more sensitive and can be more powerful in detecting CNV associations with diseases than an existing popular algorithm, especially when the CNV association signal is weak and a limited number of SNPs are located in the CNV.^

Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files

ENVISAT ASAR WSM images with pixel size 150 × 150 m, acquired in different meteorological, oceanographic and sea ice conditions were used to determined icebergs in the Amundsen Sea (Antarctica). An object-based method for automatic iceberg detection from SAR data has been developed and applied. The object identification is based on spectral and spatial parameters on 5 scale levels, and was verified with manual classification in four polygon areas, chosen to represent varying environmental conditions. The algorithm works comparatively well in freezing temperatures and strong wind conditions, prevailing in the Amundsen Sea during the year. The detection rate was 96% which corresponds to 94% of the area (counting icebergs larger than 0.03 km**2), for all seasons. The presented algorithm tends to generate errors in the form of false alarms, mainly caused by the presence of ice floes, rather than misses. This affects the reliability since false alarms were manually corrected post analysis.

Chlorophyll a concentration, and proportion of time in the water column obtained by instrumented bowhead whales

Sixty hours of direct measurements of fluorescence were collected from six bowhead whales (Balaena mysticetus) instrumented with fluorometers in Greenland in April 2005 and 2006. The data were used to (1) characterize the three-dimensional spatial pattern of chlorophyll-a (Chl-a) in the water column, (2) to examine the relationships between whale foraging areas and productive zones, and (3) to examine the correlation between whale-derived in situ values of Chl-a and those from concurrent satellite images using the NASA MODIS (Moderate Resolution Imaging Spectroradiometer) EOS-AQUA satellite (MOD21, SeaWifs analogue OC3M and SST MOD37). Bowhead whales traversed 1600 km**2, providing information on diving, Chl-a structure and temperature profiles to depths below 200 m. Feeding dives frequently passed through surface waters ( >50 m) and targeted depths close to the bottom, and whales did not always target patches of high concentrations of Chl-a in the upper 50 m. Five satellite images were available within the periods whales carried fluorometers. Whales traversed 91 pixels collecting on average 761 s (SD 826) of Chl-a samples per pixel (0-136 m). The depth of the Chl-a maximum ranged widely, from 1 to 66 m. Estimates of Chl-a made from the water-leaving radiance measurements using the OC3M algorithm were highly skewed with most samples estimated as <1 mg/m**3 Chl-a, while data collected from whales had a broad distribution with Chl-a reaching >9 mg/m**3. The correlation between the satellite-derived and whale-derived Chl-a maxima was poor, a linear fit explained only 10% of the variance.

Two pollen profiles of the middle Pleistocene at Samerberg/Upper Bavaria, Germany

Previous pollen analytical studies on sediments from the pleistocene lake basin at Samerberg, situated on the northern edge of the Bavarian Alps (47°45' N, 12°12' E, 607 m a.s.l.) had been performed on samples taken from cores and exposures close to the southern shore of the former lake. After geoelectric and refraction-seismic measurements had shown that the lake basin had been much deeper in its northern part, another core was taken where maximum depth could be expected. The corer penetrated three moraines, two of them lying above pollen-bearing sediments, and one below them, and reached the hard rock (Kössener Kalk) at a depth of 93 m. Two forest phases could be identified by pollen analysis. The pollen record begins abruptly in a forest phase at the end of a spruce-dominated period when fir started to spread (DA 1, DA = pollen zone). Following this, Abies (fir) was the main tree species at Samerberg, Picea being second, and deciduous trees were almost non-existent. First box (Buxus) was of major importance in the fir forests (DA 2), but later on beech (Fagus) and wing-nut (Pterocarya) spread (DA 3). Finally this forest gave way to a spruce forest with pine (DA 4). The beginning and the end of this interglacial cycle are not recorded. Its vegetational development is different from the eemian one known from earlier studies at Samerberg. It is characterized by the occurrence of Abies together with Buxus, Pterocarya and Fagus. A similar association of woody species is known only from the Holsteinian age deposits in an area ranging from England to Poland, though at no other place these species were such important constituents of the vegetation as at Samerberg. Therefore zone 1 to 4 are attributed to the Holsteinian interglacial period. The younger forest phase, separated from the interglacial by a stadial with open vegetation (DA 5), seems to be completely represented, though its sediments are disturbed, apparently by sliding which caused repetition of same-age-sediments in the core (DA 7a, b, c) The vegetational development is simple. A juniper phase (DA 6) was followed by reforestation with spruce, accompanied by some fir (DA 7, 9). Finally pine became the dominant species (DA 9). The simple vegetational development of this younger forest phase does not allow a safe correlation with one of the known pre-eemian interstadials, but for stratigraphical reasons it can be related best to the Dömnitz-interglacial, which among others is also known as Wacken- or Holstein-II-interglacial. Possibly another phase of reforestation is indicated at the end of the following stadial (DA 10). But due to an erosional unconformity nothing than the rise of the juniper curve can be stated. It was only after this sequence of forest phases and periods with open vegetation that glaciers reached the Samerberg area again.

Lead 210 concentrations in sediments of the Arabian Sea

In order to evaluate bioturbation in abyssal Arabian-Sea sediments of the Indus fan profiles of 210Pb (half-life: 22.3 yr) and 234Th (half-life: 24.1 d) were measured in cores collected during September and October 1995 and April 1997, respectively. The density and composition of epibenthic megafauna and lebensspuren were determined in vertical seafloor photographs during April 1997. Mean eddy-diffusive mixing coefficients according to the distribution of excess 210Pb ( 210Pb-DB) were 0.072±0.028, 0.068±0.055, 0.373±0.119, 0.037±0.009 and 0.079±0.119 cm**2 yr**-1 in the northern, western, central, eastern and southern abyssal Arabian sea, respectively. Mean eddy-diffusive mixing coefficients according to the distribution of excess 234Th (234Th-DB) were 0.53, 1.64 and 0.47 cm**2 yr**-1 in the northern, western and central abyssal Arabian Sea, respectively. Mobile epibenthic megafauna at the western, northern, central and southern study sites were dominated by ophiuroids, holothurians, ophiuroids and natant decapods (the respective densities were 100, 82, 29 and 6 individuals 1000 m**-2). The northern study site was characterized by a high abundance of spoke traces and fecal casts. The central site showed spoke traces and many tracks. The southern site displayed the highest abundance of spoke traces, whereas at the western site hardly any lebensspuren were observed. There is evidence for at least two functional endmember communities in the Arabian Sea. In the northwestern Arabian Sea (WAST) vertical particle displacement seems to be dominated by macrofauna and primarily eddy-diffusive. In the southern Arabian Sea (SAST) non-local and 'incidental' mixing due to spoke-trace producers might become more important and superimpose reduced eddy-diffusive mixing. With respect to biological data CAST is an intermediate location. Given the biological data, average 210Pb-DB is higher and decimeter-scale variability of 210Pb-DB smaller at CAST than expected. These findings indicate that in a mixture of both endmember communities the organisms may interact in way that increases values of biodiffusivity, as reflected by 210Pb-DB, and reduces decimeter-scale 210Pb-DB heterogeneity in comparison to the simple sum of the isolated effects of the endmembers. For time scales <100 years there was no evidence for a relationship between food supply (POC flux) and bioturbation intensity, as reflected by 210Pb-DB and 234Th-DB. Bioturbation intensity should be controlled primarily by the composition of the benthic fauna, its specific adaptation to the environmental setting, and the abundance of each species of the benthic community. Food supply can have only an indirect influence on bioturbation intensity. In certain parts of the ocean the a priori overall positive relationship between POC flux and biodiffusivity might include restricted intervals displaying no or even negative relations.

(Table T1) Mineralogy of ODP Leg 199 and DSDP Hole 16-162 sediments - comparison of methods

During Ocean Drilling Program Leg 199 in the equatorial Pacific, visible and near-infrared spectroscopy (VNIS) was used to measure the reflectance spectra (350-2500 nm) of 1343 sediment samples. Reflectance spectra were also measured for a suite of 60 samples of known mineralogy, thereby providing a local ground-truth calibration of spectral features to percentages of calcite, opal, smectite, and illite. The associated algorithm was used to calculate mineral percentages from the 1343 spectra. Using multiple regression and VNIS mineralogy, multisensor track physical properties and light spectroscopy data were then converted into continuous high-resolution mineralogy logs.

An Empirical Analysis of the Monetary Policy Reaction Function in India

This paper empirically analyzes India’s monetary policy reaction function by applying the Taylor (1993) rule and its open-economy version which employs dynamic OLS. The analysis uses monthly data from the period of April 1998 to December 2007. When the simple Taylor rule was estimated for India, the output gap coefficient was statistically significant, and its sign condition was found to be consistent with theoretical rationale; however, the same was not true of the inflation coefficient. When the Taylor rule with exchange rate was estimated, the coefficients of output gap and exchange rate had statistical significance with the expected signs, whereas the results of inflation remained the same as before. Therefore, the inflation rate has not played a role in the conduct of India’s monetary policy, and it is inappropriate for India to adopt an inflation-target type policy framework.

Transport costs, distance, and time : evidence from the Japanese Census of Logistics

Geographic distance is a standard proxy for transport costs under the simple assumption that freight fees increase monotonically over space. Using the Japanese Census of Logistics, this paper examines the extent to which transport distance and time affect freight costs across shipping modes, commodity groups, and prefecture pairs. The results show substantial heterogeneity in transport costs and time across shipping modes. Consistent with an iceberg formulation of transport costs, distance has a significantly positive effect on freight costs by air transportation. However, I find the puzzling results that business enterprises are likely to pay more for short-distance shipments by truck, ship, and railroad transportation. As a plausible explanation, I discuss aggregation bias arising from freight-specific premiums for timely, frequent, and small-batch shipments.

A combined measure for quantifying and qualifying the topology preservation of growing self-organizing maps

The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption about the input data distribution. The feature maps provided by this algorithm have been successfully applied for vector quantization, clustering and high dimensional data visualization processes. However, the initialization of the network topology and the selection of the SOM training parameters are two difficult tasks caused by the unknown distribution of the input signals. A misconfiguration of these parameters can generate a feature map of low-quality, so it is necessary to have some measure of the degree of adaptation of the SOM network to the input data model. The topologypreservation is the most common concept used to implement this measure. Several qualitative and quantitative methods have been proposed for measuring the degree of SOM topologypreservation, particularly using Kohonen's model. In this work, two methods for measuring the topologypreservation of the Growing Cell Structures (GCSs) model are proposed: the topographic function and the topology preserving map

A Bayesian strategy to enhance the performance of indoor localization systems

This work describes the probabilistic modelling af a Bayesian-based mechanism to improve location estimates of an already deployed location system by fusing its outputs with low-cost binary sensors. This mechanism takes advantege of the localization captabilities of different technologies usually present in smart environments deployments. The performance of the proposed algorithm over a real sensor deployment is evaluated using simulated and real experimental data.

Response timing in the lunge and target change in elite versus medium-level fencers.

The aim of the present work is to examine the differences between two groups of fencers with different levels of competition, elite and medium level. The timing parameters of the response reaction have been compared together with the kinetic variables which determine the sequence of segmented participation used during the lunge with a change in target during movement. A total of 30 male sword fencers participated, 13 elite and 17 medium level. Two force platforms recorded the horizontal component of the force and the start of the movement. One system filmed the movement in 3D, recording the spatial positions of 11 markers, while another system projected a mobile target over a screen. For synchronisation, an electronic signal enabled all the systems to be started simultaneously. Among the timing parameters of the reaction response, the choice reaction time (CRT) to the target change during the lunge was measured. The results revealed differences between the groups regarding the flight time, horizontal velocity at the end of the acceleration phase, and the length of the lunge, these being higher for the elite group, as well as other variables related to the temporal sequence of movement. No significant differences have been found in the simple reaction time or in CRT. According to the literature, the CRT appears to improve with sports practice, although this factor did not differentiate the elite from medium-level fencers. The coordination of fencing movements, that is, the right technique, constitutes a factor that differentiates elite fencers from medium-level ones.

An Efficient Hybrid GO-PWS Algorithm to Analyze Conformal Serrated-Edge Reflectors for Millimeter-Wave Compact Range

A method to analyze parabolic reflectors with arbitrary piecewise rim is presented in this communication. This kind of reflectors, when operating as collimators in compact range facilities, needs to be large in terms of wavelength. Their analysis is very inefficient, when it is carried out with fullwave/MoM techniques, and it is not very appropriate for designing with PO techniques. Also, fast GO formulations do not offer enough accuracy to reach performance results. The proposed algorithm is based on a GO-PWS hybrid scheme, using analytical as well as non-analytical formulations. On one side, an analytical treatment of the polygonal rim reflectors is carried out. On the other side, non-analytical calculi are based on efficient operations, such as M2 order 2-dimensional FFT. A combination of these two techniques in the algorithm ensures real ad-hoc design capabilities, reached through analysis speedup. The purpose of the algorithm is to obtain an optimal conformal serrated-edge reflector design through the analysis of the field quality within the quiet zone that it is able to generate in its forward half space.

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.