Predicting smoking cessation and its relapse in HIV-infected patients: the Swiss HIV Cohort Study

OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.

Study of Heavy-ion Induced Fission for Heavy Element Synthesis

Fission fragment mass distributions were measured in heavy-ion induced fission of 238U. The mass distributions changed drastically with incident energy. The results are explained by a change of the ratio between fusion and quasifission with nuclear orientation. A calculation based on a fluctuation dissipation model reproduced the mass distributions and their incident energy dependence. Fusion probability was determined in the analysis. Evaporation residue cross sections were calculated with a statistical model for the reactions of 30Si+238U and 34S+238U using the obtained fusion probability in the entrance channel. The results agree with the measured cross sections of 263,264Sg and 267,268Hs, produced by 30Si+238U and 34S+238U, respectively. It is also suggested that sub-barrier energies can be used for heavy element synthesis.

Trends of mean and extreme temperature indices since 1874 at low-elevation sites in the Southern Alps

We describe the recovery of three daily meteorological records for the southern Alps (Domodossola, Riva del Garda, and Rovereto), all starting in the second half of the nineteenth century. We use these new data, along with additional records, to study regional changes in the mean temperature and extreme indices of heat waves and cold spells frequency and duration over the period 1874–2015. The records are homogenized using subdaily cloud cover observations as a constraint for the statistical model, an approach that has never been applied before in the literature. A case study based on a record of parallel observations between a traditional meteorological window and a modern screen shows that the use of cloud cover can reduce the root-mean-square error of the homogenization by up to 30% in comparison to an unaided statistical correction. We find that mean temperature in the southern Alps has increased by 1.4°C per century over the analyzed period, with larger increases in daily minimum temperatures than maximum temperatures. The number of hot days in summer has more than tripled, and a similar increase is observed in duration of heat waves. Cold days in winter have dropped at a similar rate. These trends are mainly caused by climate change over the last few decades.

Predicting the Fed

Predicting the federal funds rate and beating the federal funds futures market: mission impossible? Not so. We employ a Markov transition process and show that this model outperforms the federal funds futures market in predicting the target federal funds rate. Thus, by using purely historical data we are able to better explain future monetary policy than a forward looking measure like the federal funds futures rate. The fact that the federal funds futures market can be beaten by a statistical model, suggests that the federal funds futures market lacks eciency. The mar- ket allocates too much weight to current Federal Reserve communication and other real-time macro events, and allocates too little weight to past monetary policy behavior.

Assessment of occupational exposures to organic chemicals in a plastics manufacturing facility

The objective of this dissertation was to design and implement strategies for assessment of exposures to organic chemicals used in the production of a styrene-butadiene polymer at the Texas Plastics Company (TPC). Linear statistical retrospective exposure models, univariate and multivariate, were developed based on the validation of historical industrial hygiene monitoring data collected by industrial hygienists at TPC, and additional current industrial hygiene monitoring data collected for the purposes of this study. The current monitoring data served several purposes. First, it provided information on current exposure data, in the form of unbiased estimates of mean exposure to organic chemicals for each job title included. Second, it provided information on homogeneity of exposure within each job title, through the use of a carefully designed sampling scheme which addressed variability of exposure both between and within job titles. Third, it permitted the investigation of how well current exposure data can serve as an evaluation tool for retrospective exposure estimation. Finally, this dissertation investigated the simultaneous evaluation of exposure to several chemicals, as well as the use of values below detection limits in a multivariate linear statistical model of exposures. ^

AN ANALYSIS OF THE GENERAL WELL-BEING OF BLACKS AND WHITES

The importance of race as a factor in mental health status has been a topic of controversy. This study reviews the history of research in this area and examines racial variances in the relationship between selected socio-demographic variables and general well-being. The study also examines the appropriateness of an additive versus an interactive statistical model for this investigation.^ The sample consists of 6,913 persons who completed the General Well-Being Schedules as administered in the detailed component of the first National Health and Nutrition Examination Survey (NHANES I) conducted by the National Center for Health Statistics between April, 1971 and October, 1975. The sampling design is a multistage, probability sample of clusters of persons in area based segments. Of the 6,913 persons, 873 are Black.^ Unlike other recent community based mental health studies, this study revealed significant differences between the general well-being of Blacks and Whites. Blacks continued to exhibit significantly lower levels of well-being even after adjustments were made for income, education, marital status, sex, age and place of residence. Statistical interaction was found between race and sex with Black females reporting lower levels of well-being than either Black or White males or their White female counterparts.^ The study includes a detailed review of the NHANES I sample design. It is shown that selected aspects of the design make it difficult to render appropriate national comparisons of Black-White differences. As a result conclusions pertaining to these differences based on NHANES I may be of questionable validity. ^

THE CHLOREX TREATABILITY STUDY: ENVIRONMENTAL FATE IN FACULTATIVE ANAEROBIC AND AEROBIC WASTE STABILIZATION PONDS (BIODEGRADATION, VOLATILIZATION, SORPTION, PRIORITY POLLUTANTS)

The efficacy of waste stabilization lagoons for the treatment of five priority pollutants and two widely used commercial compounds was evaluated in laboratory model ponds. Three ponds were designed to simulate a primary anaerobic lagoon, a secondary facultative lagoon, and a tertiary aerobic lagoon. Biodegradation, volatilization, and sorption losses were quantified for bis(2-chloroethyl) ether, benzene, toluene, naphthalene, phenanthrene, ethylene glycol, and ethylene glycol monoethyl ether. A statistical model using a log normal transformation indicated biodegradation of bis(2-chloroethyl) ether followed first-order kinetics. Additionally, multiple regression analysis indicated biochemical oxygen demand was the water quality variable most highly correlated with bis(2-chloroethyl) ether effluent concentration. ^

Alpine permafrost index map

The objective of this study is the production of an Alpine Permafrost Index Map (APIM) covering the entire European Alps. A unified statistical model that is based on Alpine-wide permafrost observations is used for debris and bedrock surfaces across the entire Alps. The explanatory variables of the model are mean annual air temperatures, potential incoming solar radiation and precipitation. Offset terms were applied to make model predictions for topographic and geomorphic conditions that differ from the terrain features used for model fitting. These offsets are based on literature review and involve some degree of subjective choice during model building. The assessment of the APIM is challenging because limited independent test data are available for comparison and these observations represent point information in a spatially highly variable topography. The APIM provides an index that describes the spatial distribution of permafrost and comes together with an interpretation key that helps to assess map uncertainties and to relate map contents to their actual expression in terrain. The map can be used as a first resource to estimate permafrost conditions at any given location in the European Alps in a variety of contexts such as research and spatial planning. Results show that Switzerland likely is the country with the largest permafrost area in the Alps, followed by Italy, Austria, France and Germany. Slovenia and Liechtenstein may have marginal permafrost areas. In all countries the permafrost area is expected to be larger than the glacier-covered area.

Relación precipitación-escorrentía y número de curva bajo diferentes condiciones de uso del suelo: : cuenca modal del sistema serrano de La Ventana, Argentina

La metodología del número de la curva (NC) es la más empleada para transformar la precipitación total en precipitación efectiva. De esta manera se constituye en una herramienta de gran valor para realizar estudios hidrológicos en cuencas hidrográficas, fundamentalmente cuando hay una deficiencia de registros extensos y confiables. Esta metodología requiere del conocimiento del tipo y uso de suelo de la cuenca en estudio y registros pluviográficos. En el presente trabajo se aplicó el procesamiento de imágenes LANDSAT para la zonificación de la vegetación y uso del suelo en la cuenca del Arroyo Pillahuinco Grande (38° LS y 61° 15' LW), ubicada sobre el sistema serrano de La Ventana, en el sudoeste de la provincia de Buenos Aires, Argentina. El análisis de su interrelación generó los valores de NC y coeficiente de escorrentía (CE). El procesamiento digital de la base de datos raster georreferenciada se realizó con aplicación de herramientas de sistema de información geográfica (Idrisi Kilimanjaro). El análisis de regresión múltiple efectuado a las variables generó un R2 que explica el 89,77 % de la variabilidad de CE (a < 0,01). Los resultados se exponen a nivel diagnóstico y zonificación del NC, donde la mayor influencia de la escorrentía se relaciona con las variables cobertura vegetal y uso del suelo.

Photosynthetic parameters, chlorophyll concentration, and diffuse attenuation coefficients in the Rhode River, Maryland (USA), 1990-2009

Parameters in the photosynthesis-irradiance (P-E) relationship of phytoplankton were measured at weekly to bi-weekly intervals for 20 yr at 6 stations on the Rhode River, Maryland (USA). Variability in the light-saturated photosynthetic rate, PBmax, was partitioned into interannual, seasonal, and spatial components. The seasonal component of the variance was greatest, followed by interannual and then spatial. Physiological models of PBmax based on balanced growth or photoacclimation predicted the overall mean and most of the range, but not individual observations, and failed to capture important features of the seasonal and interannual variability. PBmax correlated most strongly with temperature and the concentration of dissolved inorganic carbon (IC), with lesser correlations with chlorophyll a, diffuse attenuation coefficient, and a principal component of the species composition. In statistical models, temperature and IC correlated best with the seasonal pattern, but temperature peaked in late July, out of phase with PBmax, which peaked in September, coincident with the maximum in monthly averaged IC concentration. In contrast with the seasonal pattern, temperature did not contribute to interannual variation, which instead was governed by IC and the additional lesser correlates. Spatial variation was relatively weak and uncorrelated with ancillary measurements. The results demonstrate that both the overall distribution of PBmax and its relationship with environmental correlates may vary from year to year. Coefficients in empirical statistical models became stable after including 7 to 10 yr of data. The main correlates of PBmax are amenable to automated monitoring, so that future estimates of primary production might be made without labor-intensive incubations.

Do electricity supply constraints matter for comparative advantage? : a neoclassical approach

This paper examines the extent to which electricity supply constraints could affect sectoral specialization. For this purpose, an empirical trade model is estimated from 1990-2008 panel data on 15 OECD countries and 12 manufacturing sectors. We find that along with Ricardian technological differences and Heckscher-Ohlin factor-endowment differences, productivity-adjusted electricity capacity drives sectoral specialization in several sectors. Among them, electrical equipment, transport equipment, machinery, chemicals, and paper products will see lower output shares as a result of decreases in productivity-adjusted electricity capacity. Furthermore, our dynamic panel estimation reveals that the effects of Ricardian technological differences dominate in the short-run, and factor endowment differences and productivity-adjusted electricity capacity tend to have a significant effect in only the long-run.

Governance Structure Choices in Supply Chain Management Evidence from Spanish and Chinese Pork Chain Cases

The author participated in the 6 th EU Framework Project ―Q-pork Chains (FP6-036245-2)‖ from 2007 to 2009. With understanding of work reports from China and other countries, it is found that compared with other countries, China has great problems in pork quality and safety. By comparing the pork chain management between China and Spain, It is found that the difference in governance structure is one of the main differences in pork chain management between Spain and China. In China, spot-market relationship still dominates governance structure of pork chain, especially between the numerous house-hold pig holders and the great number of small slaughters. While in Spain, chain agents commonly apply cooperatives or integrations to cooperate. It also has been proven by recent studies, that in quality management at the chain level that supply chain integration has a direct effect on quality management practices (Han, 2010). Therefore, the author started to investigate the governance structure choices in supply chain management. And it has been set as the first research objective, which is to explain the governance structure choices process and the influencing factors in supply chain management, analyzing the pork chains cases in Spain and in China. During the further investigation, the author noticed the international trade of pork between Spain and China is not smooth since the signature of bi-lateral agreement on pork trade in 2007. Thus, another objective of the research is to find and solve the problems exist in the international pork chain between Spain and China. For the first objective, to explain the governance structure choices in supply chain management, the thesis conducts research in three main sections. 10 First of all, the thesis gives a literature overview in chapter two on Supply Chain Management (SCM), agri-food chain management and pork chain management. It concludes that SCM is a systems approach to view the supply chains as a whole, and to manage the total flow of goods inventory from the supplier to the ultimate customer. It includes the bi-directional flow of products (materials and services) and information, and the associated managerial and operational activities. And it also is a customer focus to create unique and individual source of customer value with an appropriate use of resources, leading to customer satisfaction and building competitive chain advantages. Agri-food chain management and pork chain management are applications of SCM in agri-food sector and pork sector respectively. Then, the research gives a comparative study in chapter three in the pork chain and pork chain management between Spain and China. Many differences are found, while the main difference is governance structure in pork chain management. Furthermore, the author gives an empirical study on governance structure choice in chapter five. It is concluded that governance structure of supply chain consists of a collection of rules/institutions/constraints structuring the transactions between the various stakeholders. Based on the overview on literatures closely related with governance structure, such as transaction cost economics, transaction value analysis and resource-based view theories, seven hypotheses are proposed, which are: Hypothesis 1: Transaction cost has positive relationship with governance structure choice Hypothesis 2: Uncertainty has positive relationship with transaction cost; higher uncertainty exerts high transaction cost Hypothesis 3: The relationship between asset specificity and transaction cost is positive Hypothesis 4: Collaboration advantages and governance structure choice have positive relationship11 Hypothesis 5: Willingness to collaborate has positive relationship with collaboration advantages Hypothesis 6: Capability to collaborate has positive relationship with collaboration advantages Hypothesis 7: Uncertainty has negative effect on collaboration advantages It is noted that as transaction cost value is negative, the transaction cost mentioned in the hypotheses is its absolute value. To test the seven hypotheses, Structural Equation Model (SEM) is applied and data collected from 350 pork slaughtering and processing companies in Jiangsu, Shandong and Henan Provinces in China is used. Based on the empirical SEM model and its results, the seven hypotheses are proved. The author generates several conclusions accordingly. It is found that the governance structure choice of the chain not only depends on transaction cost, it also depends on collaboration advantages. Exchange partners establish more stable and more intense relationship to reduce transaction cost and to maximize collaboration advantages. ―Collaboration advantages‖ in this thesis is defined as the joint value achieved through transaction (mutual activities) of agents in supply chains. This value forms as improvements, mainly in mutual logistics systems, cash response, information exchange, technological improvements and innovative improvements and quality management improvements, etc. Governance structure choice is jointly decided by transaction cost and collaboration advantages. Chain agents take different governance structures to coordinate in order to decrease their transaction cost and to increase their collaboration advantages. In China´s pork chain case, spot market relationship dominates the governance structure among the numerous backyard pig farmer and small family slaughterhouse 12 as they are connected by acquaintance relationship and the transaction cost in turn is low. Their relationship is reliable as they know each other in the neighborhood; as a result, spot market relationship is suitable for their exchange. However, the transaction between large-scale slaughtering and processing industries and small-scale pig producers is becoming difficult. The information hold back behavior and hold-up behavior of small-scale pig producers increase transaction cost between them and large-scale slaughtering and processing industries. Thus, through the more intense and stable relationship between processing industries and pig producers, processing industries reduce the transaction cost and improve the collaboration advantages with their chain partners, in which quality and safety collaboration advantages be increased, meaning that processing industries are able to provide consumers products with better quality and higher safety. It is also drawn that transaction cost is influenced mainly by uncertainty and asset specificity, which is in line with new institutional economics theories developed by Williamson O. E. In China´s pork chain case, behavioral uncertainty is created by the hold-up behaviors of great numbers of small pig producers, while big slaughtering and processing industries having strong asset specificity. On the other hand, ―collaboration advantages‖ is influenced by chain agents´ willingness to collaborate and chain agents´ capabilities to cooperate. With the fast growth of big scale slaughtering and processing industries, they are more willing to know and make effort to cooperate with their chain members, and they are more capable to create joint value together with other chain agents. Therefore, they are now the main chain agents who drive more intense and stable governance structure in China‘s pork chain. For the other objective, to find and solve the problems in the international pork chain between Spain and China, the research gives an analysis in chapter four on the 13 international pork chain. This study gives explanations why the international trade of pork between Spain and China is not sufficient from the chain perspective. It is found that the first obstacle is the high quality and safety requirement set by Chinese government. It makes the Spanish companies difficult to get authorities to export. Other aspects, such as Spanish pork is not competitive in price compared with other countries such as Denmark, United States, Canada, etc., Chinese consumers do not have sufficient information on Spanish pork products, are also important reasons that Spain does not export great quantity of pork products to China. It is concluded that China´s government has too much concern on the quality and safety requirements to Spanish pork products, which makes trade difficult to complete. The two countries need to establish a more stable and intense trade relationship. They also should make the information exchange sufficient and efficient and try to break trade barriers. Spanish companies should consider proper price strategies to win the Chinese pork market

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.

Reliability analysis based on non-dimensional parameters

A reliability analysis method is proposed that starts with the identification of all variables involved. These are divided in three groups: (a) variables fixed by codes, as loads and strength project values, and their corresponding partial safety coefficients, (b) geometric variables defining the dimension of the main elements involved, (c) the cost variables, including the possible damages caused by failure, (d) the random variables as loads, strength, etc., and (e)the variables defining the statistical model, as the family of distribution and its corresponding parameters. Once the variables are known, the II-theorem is used to obtain a minimum equivalent set of non-dimensional variables, which is used to define the limit states. This allows a reduction in the number of variables involved and a better understanding of their coupling effects. Two minimum cost criteria are used for selecting the project dimensions. One is based on a bounded-probability of failure, and the other on a total cost, including the damages of the possible failure. Finally, the method is illustrated by means of an application.

Predicción del remonte extremo en playas : aplicación a los sectores litorales de la costa española

El remonte extremo o remonte del 2% es un parámetro clave en la ingeniería costera dado que permite acometer actuaciones en las playas bajo criterios de sostenibilidad económico y socioambiental. Estas actuaciones van desde el diseño de estructuras en el trasdós de la playa a planes de actuación urbanística en la costa tal que se determine adecuadamente los límites de dominio público. El adecuado diseño de estas actuaciones adquiere más relevancia hoy en día debido a las nuevas amenazas que se ponen de relieve debido al cambio climático, y que en el caso concreto de la costa se materializa en inundaciones que provocan pérdidas económicas. Estudios precedentes han realizado ensayos in situ o en modelo físico para la determinación del remonte extremo en playas. Al comparar estas formulaciones la dispersión es alta lo que implica que la precisión en la obtención del remonte no sea suficiente. Esta dispersión se justifica debido al amplio espectro de playas existentes y la alta variabilidad del clima marítimo. Este problema cobra más relevancia debido a las actuaciones preventivas o correctivas a acometer frente al cambio climático bajo un criterio de sostenibilidad. Con el fin de realizar actuaciones sostenibles bajo el contexto actual del probable aumento de inundaciones costeras por cambio climático no deben obtenerse ni magnitudes sobredimensionadas con el consecuente consumo de recursos y afección a las actividades económicas, ni magnitudes subestimadas que pongan en riesgo la estabilidad y/o la funcionalidad de las actuaciones para un periodo de diseño. El principal objetivo de esta tesis es proponer una formulación de aplicación en la obtención del remonte extremo tal que se cumplan los criterios de seguridad para el servicio y funcionalidad de la obra y los criterios de sostenibilidad económico y socio-ambiental que se requieren hoy en día. Es decir, una fórmula que no sobredimensione el cálculo de este valor pero que pueda cubrir la casuística que acontece en las distintas tipologías de playas. Complementariamente a este objetivo se ejemplifica la aplicación de estas formulaciones en casos reales tal que se reduzca la incertidumbre y ambigüedad en la obtención de las variables independientes de las formulaciones. Para la consecución de estos objetivos se realiza un estado del arte en el que se estudia tanto los estudios estadísticos en la obtención de este parámetro como los modelos numéricos propuestos para ello, tal que se deduzca la mejor línea de investigación en la consecución del fin de esta tesis. Tras este estudio del arte se concluye que la mejor línea de investigación sigue la vía estadística y se diseña un modelo físico con fondo de arena en contraste con modelos físicos con fondo impermeable fijo. Los resultados de dicho modelo se han comparado con las formulaciones precedentes y se proponen las fórmulas de aplicación más convenientes para la obtención del remonte extremo. Complementariamente a la propuesta de formulaciones se desarrolla una metodología de aplicación de dichas formulaciones a casos de la costa española que ejemplifican convenientemente su uso para una adecuada predicción de este valor en las playas. The extreme runup is a key parameter in coastal management. This parameter allows to develop sustainability actions at the coast that meet economical and environmental criteria. At the coast the actions can be either design of structures at the shore or actions plans delimiting reclamation areas. The climate change has given more relevance to accomplish an appropriate design for the coastal management actions. At the coast the threaten are mainly focused on more frequent floods that cause economic losses. Previous studies have carried out field or physical model experiments to accomplish an equation for the extreme runup prediction. Although dispersion remains high when comparing the different proposals so the accuracy in the prediction might be risky. This scattering comes from the wide sort of beaches and the high variability of the maritime climate. The new actions that are needed to develop to counteract the effects of the climate change need a more efficient criteria. Hence formulations should not overestimate or underestimate the values of the extreme runup. The overestimation implies to consume resources that are not needed and the underestimation means in a structure risk to support safely the loads. The main goal of this thesis is to propose a formulation for the extreme runup prediction so the safety of the structure can be accomplished but at the same time the sustainability of the action is ensured under economical and environmental criteria that are demanded nowadays. So the formulation does not overestimate the extreme value but cover with enough confidence the different sort of beaches. The application of the formulation is also explained in order to reduce uncertainty when the input values are obtained. In order to accomplish the goal of this research firstly a literature review is done. Statistical and numerical models are studied. The statistical model is selected as the most convenient research guideline. In order to obtain runup results a physical model with sand bed is carried out. The bed differs from those that used impermeable slope in previous experiments. Once the results are obtained they are compared with the previous equations and a final formulation is proposed. Finally a methodology to apply the deduced formulation to the Spanish beaches is addressed.