Atmospheric pollution: influence on hospital admissions in paediatric rheumatic diseases

Objective: To investigate the lag structure effects from exposure to atmospheric pollution in acute outbursts in hospital admissions of paediatric rheumatic diseases (PRDs). Methods: Morbidity data were obtained from the Brazilian Hospital Information System in seven consecutive years, including admissions due to seven PRDs (juvenile idiopathic arthritis, systemic lupus erythematosus, dermatomyositis, Henoch-Schonlein purpura, polyarteritis nodosa, systemic sclerosis and ankylosing spondylitis). Cases with secondary diagnosis of respiratory diseases were excluded. Daily concentrations of inhaled particulate matter (PM10), sulphur dioxide (SO2) nitrogen dioxide (NO2), ozone (O-3) and carbon monoxide (CO) were evaluated. Generalized linear Poisson regression models controlling for short-term trend, seasonality, holidays, temperature and humidity were used. Lag structures and magnitude of air pollutants' effects were adopted to estimate restricted polynomial distributed lag models. Results: The total number of admissions due to acute outbursts PRD was 1,821. The SO2 interquartile range (7.79 mu g/m(3)) was associated with an increase of 1.98% (confidence interval 0.25-3.69) in the number of hospital admissions due to outcome studied after 14 days of exposure. This effect was maintained until day 17. Of note, the other pollutants, with the exception of O-3, showed an increase in the number of hospital admissions from the second week. Conclusion: This study is the first to demonstrate a delayed association between SO2 and PRD outburst, suggesting that oxidative stress reaction could trigger the inflammation of these diseases. Lupus (2012) 21, 526-533.

Study of the components of quality in SO2-free wines obtained by innovative vinification protocols. Evaluation of the pre-fermentative addition of lysozyme and oenological tannins.

The research performed during the PhD candidature was intended to evaluate the quality of white wines, as a function of the reduction in SO2 use during the first steps of the winemaking process. In order to investigate the mechanism and intensity of interactions occurring between lysozyme and the principal macro-components of musts and wines, a series of experiments on model wine solutions were undertaken, focusing attention on the polyphenols, SO2, oenological tannins, pectines, ethanol, and sugar components. In the second part of this research program, a series of conventional sulphite added vinifications were compared to vinifications in which sulphur dioxide was replaced by lysozyme and consequently define potential winemaking protocols suitable for the production of SO2-free wines. To reach the final goal, the technological performance of two selected yeast strains with a low aptitude to produce SO2 during fermentation were also evaluated. The data obtained suggested that the addition of lysozyme and oenological tannins during the alcoholic fermentation could represent a promising alternative to the use of sulphur dioxide and a reliable starting point for the production of SO2-free wines. The different vinification protocols studied influenced the composition of the volatile profile in wines at the end of the alcoholic fermentation, especially with regards to alcohols and ethyl esters also a consequence of the yeast’s response to the presence or absence of sulphites during fermentation, contributing in different ways to the sensory profiles of wines. In fact, the aminoacids analysis showed that lysozyme can affect the consumption of nitrogen as a function of the yeast strain used in fermentation. During the bottle storage, the evolution of volatile compounds is affected by the presence of SO2 and oenological tannins, confirming their positive role in scaveging oxygen and maintaining the amounts of esters over certain levels, avoiding a decline in the wine’s quality. Even though a natural decrease was found on phenolic profiles due to oxidation effects caused by the presence of oxygen dissolved in the medium during the storage period, the presence of SO2 together with tannins contrasted the decay of phenolic content at the end of the fermentation. Tannins also showed a central role in preserving the polyphenolic profile of wines during the storage period, confirming their antioxidant property, acting as reductants. Our study focused on the fundamental chemistry relevant to the oxidative phenolic spoilage of white wines has demonstrated the suitability of glutathione to inhibit the production of yellow xanthylium cation pigments generated from flavanols and glyoxylic acid at the concentration that it typically exists in wine. The ability of glutathione to bind glyoxylic acid rather than acetaldehyde may enable glutathione to be used as a ‘switch’ for glyoxylic acid-induced polymerisation mechanisms, as opposed to the equivalent acetaldehyde polymerisation, in processes such as microoxidation. Further research is required to assess the ability of glutathione to prevent xanthylium cation production during the in-situ production of glyoxylic acid and in the presence of sulphur dioxide.

Identifizierung biogene Amine bildender Bakterien und Einsatz von Enzymen zur Hemmung ihres Wachstums während der Weinbereitung

Mikroorganismen spielen eine wichtige Rolle in der Weinherstellung. Neben ihren positiven Stoffwechselaktivitäten wie die Bildung von Ethanol während der alkoholischen Gärung sind vor allem Bakterien in der Lage, Weinfehler zu verursachen. Einer dieser Weinfehler ist die Produktion von biogenen Aminen. Diese niedermolekularen Stickstoffverbindungen können zu verschiedenen Gesundheitsproblemen wie Bluthochdruck und Migräne führen. Aufgrund von hohen Ethanolgehalten und dem Vorkommen verschiedener biogener Amine kommt es im Wein zu einer Verstärkung dieser physiologischen Effekte. Um die Bildung dieser Verbindungen zu verhindern, ist es von speziellem Interesse, die verantwortlichen Mikroorganismen zu identifizieren und sie in ihrem Wachstum zu hemmen.In einem Teil der Dissertation stand die Isolierung und Identifizierung biogener Amine produzierender Bakterien aus deutschen Jungweinen und Mosten im Vordergrund. Es konnte gezeigt werden, dass hauptsächlich Milchsäurebakterien als potenzielle Produzenten in Frage kommen. Diese Bakteriengruppe war in hohen Titern in nahezu allen Proben vorhanden und stellt somit eine potentielle Gefahr für die Weinbereitung dar. Zur Identifizierung der Isolate wurden verschiedene molekularbiologische Methoden wie specifically amplified DNA polymorphic-PCR (Fingerprintmethode), Multiplex-PCR oder 16S rDNA-Sequenzierung angewandt. Das Screening bezüglich der Bildung von biogenen Aminen erfolgte mit Hilfe einer im Rahmen dieser Arbeit entwickelten hochauflösenden Dünnschichtchromatographie gefolgt von der Quantifizierung mittels HPLC.Zur Wachstumshemmung dieser Schadbakterien wurden zwei Exoenzyme aus Streptomyces albidoflavus B578 isolieren. Diese Enzyme wurden gereinigt und als eine Muramidase und eine Protease identifiziert. Aktivitätstests konnten zeigen, dass diese Enzyme eine hohe lytische Wirkung gegen weinrelevante Mikroorganismen aufweisen. Ebenso war die Aktivität der Enzyme unter Weinbedingungen sehr stabil. Aufgrund dieser Ergebnisse könnten diese Enzyme eine mögliche Alternative zur Zugabe von Lysozym oder Schwefeldioxid sein, welche konventionell in der Weinbereitung ihren Einsatz finden.

Observations of volcanic emissions using satellite remote sensing

Volcanoes pose a threat to the human population at regional and global scales and so efficient monitoring is essential in order to effectively manage and mitigate the risks that they pose. Volcano monitoring from space has been possible for over thirty years and now, more than ever, a suite of instruments exists with the capability to observe emissions of gas and ash from a unique perspective. The goal of this research is to demonstrate the use of a range of satellite-based sensors in order to detect and quantify volcanic sulphur dioxide, and to assess the relative performances of each sensor against one another. Such comparisons are important in order to standardise retrievals and permit better estimations of the global contribution of sulphur dioxide to the atmosphere from volcanoes for climate modelling. In this work, retrievals of volcanic sulphur dioxide from a number of instruments are compared, and the individual performances at quantifying emissions from large, explosive volcanic eruptions are assessed. Retrievals vary widely from sensor to sensor, and often the use of a number of sensors in synergy can provide the most complete picture, rather than just one instrument alone. Volcanic emissions have the ability to result significant economic loses by grounding aircraft due to the high risk associated with ash encountering aircraft. As sulphur dioxide is often easier to measure than ash, it is often used as a proxy. This work examines whether this is a reasonable assumption, using the Icelandic eruption in early 2010 as a case study. Results indicate that although the two species are for the most part collocated, separation can occur under some conditions, meaning that it is essential to accurately measure both species in order to provide effective hazard mitigation. Finally, the usefulness of satellite remote sensing in quantifying the passive degassing from Turrialba, Costa Rica is demonstrated. The increase in activity from 2005 – 2010 can be observed in satellite data prior to the phreatic phase of early 2010, and can therefore potentially provide a useful indication of changing activity at some volcanoes.

Climate Engineering: gesellschaftliches Konfliktpotenzial und öffentliche Partizipationsmöglichkeiten

Aufbauend auf den Ergebnissen einer Literatur- und Medienanalyse wurde erstmals zum Thema Climate Engineering ein sogenanntes Gruppen-Delphi durchgeführt, um aktuelle und argumentativ fundierte Einschätzungen von Experten zu den möglichen sozialen und kulturellen Folgen von Climate Engineering, insbesondere auch in Deutschland, zu erhalten. Die Ergebnisse dieser diskursiven Form der Expertenbefragung zeigen deutlich, dass die Verfahren des Climate Engineering differenziert betrachtet und bewertet werden müssen. Auf Akzeptanzprobleme stoßen vor allem Maßnahmen, bei denen hohe Unsicherheit über die potenziellen Nebenwirkungen besteht. In der Literatur und unter den Experten besteht Einigkeit darüber, dass es bereits jetzt, in der Frühphase der Entwicklung von Climate Engineering-Strategien, notwendig sei, die Bürger über diese Technologien und Strategien aufzuklären.

Antarctic Volcanic Flux Ratios from Law Dome Ice Cores

Explosive volcanic eruptions can inject large quantities of sulphur dioxide into the stratosphere. The aerosols that result from oxidation of the sulphur dioxide can produce significant cooling of the troposphere by reflecting or absorbing solar radiation. It is possible to obtain an estimate of the relative stratospheric sulphur aerosol concentration produced by different volcanoes by comparing sulphuric acid fluxes determined by analysis of polar ice cores. Here, we use a non-sea-salt sulphate time series derived from three well-dated Law Dome ice cores to investigate sulphuric acid flux ratios for major eruptions over the period AD 1301-1995. We use additional data from other cores to investigate systematic spatial variability in the ratios. Only for the Kuwae eruption (Law Dome ice date AD 1459.5) was the H2SO4 flux larger than that deposited by Tambora (Law Dome ice date AD 1816.7).

Un método fotocolorimétrico para la determinación de alcohol en vinos

Se describe un método fotocolorimétrico para la determinación de alcohol en vinos basado en la medida del cambio de color que sufre el bicromato de potasio durante la oxidación de esa sustancia orgánica. El frasco de reacción descripto permite efectuar la destilación del alcohol en la medida directa del color sin necesidad de verter el líquido reactivo a otro recipiente. El anhídrido sulfuroso no tiene influencia apreciable en los resultados obtenidos, y no se hace necesaria la neutralización previa de la muestra. Como es de esperar, tampoco el ácido acético influye en las determinaciones. El método ofrece una precisión considerable y esta circunstancia, unida a la sencillez de las manipulaciones, lo hacen aconsejable en diversos casos.

(Table 1.5) Contents of some volatile components in glassy MORB from the north part of the Bougault anomaly, Mid-Atlantic Ridge 15°N

Structure and composition of sub-surface bottom sediments from the southwest Barents Sea have been under study. The study has revealed heterogeneity of sediment structure resulted from temporal irregularity and variability of sedimentation processes. The study of the heavy minerals from 0.1-0.01 mm grain size fraction has shown prevalence of green hornblende, epidote, garnet, and ilmenite in all types of sediments; these minerals are the basis of terrigenous-mineralogical province. At the same time in different areas local terrigenous-mineralogical associations have been identified. Clay mineral composition of in the sediments was quite uniform: biotite, chlorite, hydromica, smectite. Despite this, a number of features indicating initial stages of clay mineral transformation has been identified. Differences in material composition and structure of the studied sediments are associated with rapid change in paleogeographic situation on the land - ice cover melting on the Kola Peninsula and subsequent Holocene climatic situation.

Minerals and geochemistry of DSDP Hole 81-552A

The acid insoluble coarse fractions of the glacial-interglacial sequence of Hole 552A in the NE Atlantic are made up of varying amounts of terrigenous detritus, biogenic silica, and pyroclastic material, principally volcanic glass. Volcanic ash content varies significantly over the entire interval, and the three North Atlantic ash horizons of Ruddiman and Glover (1972) can be recognized satisfactorily. The terrigenous detritus is of mixed metamorphic-basaltic type and probably originated on the Greenland landmass

Chemistry of serpentinized peridotites from ODP Hole 109-670A

In this paper we describe textural relationships in hydrated upper mantle peridotites emplaced at a nonconstructive ridge segment. Development of serpentinites and partially serpentinized peridotites takes place in four main stages: (1) pervasive serpentinization forming mainly lizardite, (2) a tensional stage forming chrysotile + talc + chlorite, (3) a deformational stage forming antigorite + tremolite, and (4) a late local tensional stage forming another generation of chrysotile veinlets. Mineral chemistry of serpentine pseudomorphs reflects in part primary mineral compositions. Olivine pseudomorphs are typically nickeliferous and depleted in aluminum and chromium. Orthopyroxene pseudomorphs have lower nickel contents and relatively high iron, aluminum, and chromium contents. Clinopyroxene pseudomorphs have very low nickel contents and relatively high aluminum and chromium contents. These chemical patterns in the serpentinites can be used to help discriminate between harzburgitic and lherzolitic protoliths. Oxygen isotopes and mineral parageneses suggest serpentine is derived from circulation of hydrothermal (200?C) fluids through the peridotite body. Crystallization of tremolite, talc, and chlorite may have occurred at temperatures up to 525?C if C02/H20 ratios were less than 0.25. Open fissures developing in aging upper mantle provide paths for important seawater circulation through a thin basaltic carapace down to shallow mantle rocks.

Aplicación de técnicas de inteligencia artificial a la predicción de contaminantes atmosféricos

Abstract Air pollution is a big threat and a phenomenon that has a specific impact on human health, in addition, changes that occur in the chemical composition of the atmosphere can change the weather and cause acid rain or ozone destruction. Those are phenomena of global importance. The World Health Organization (WHO) considerates air pollution as one of the most important global priorities. Salamanca, Gto., Mexico has been ranked as one of the most polluted cities in this country. The industry of the area led to a major economic development and rapid population growth in the second half of the twentieth century. The impact in the air quality is important and significant efforts have been made to measure the concentrations of pollutants. The main pollution sources are locally based plants in the chemical and power generation sectors. The registered concerning pollutants are Sulphur Dioxide (SO2) and particles on the order of ∼10 micrometers or less (PM10). The prediction in the concentration of those pollutants can be a powerful tool in order to take preventive measures such as the reduction of emissions and alerting the affected population. In this PhD thesis we propose a model to predict concentrations of pollutants SO2 and PM10 for each monitoring booth in the Atmospheric Monitoring Network Salamanca (REDMAS - for its spanish acronym). The proposed models consider the use of meteorological variables as factors influencing the concentration of pollutants. The information used along this work is the current real data from REDMAS. In the proposed model, Artificial Neural Networks (ANN) combined with clustering algorithms are used. The type of ANN used is the Multilayer Perceptron with a hidden layer, using separate structures for the prediction of each pollutant. The meteorological variables used for prediction were: Wind Direction (WD), wind speed (WS), Temperature (T) and relative humidity (RH). Clustering algorithms, K-means and Fuzzy C-means, are used to find relationships between air pollutants and weather variables under consideration, which are added as input of the RNA. Those relationships provide information to the ANN in order to obtain the prediction of the pollutants. The results of the model proposed in this work are compared with the results of a multivariate linear regression and multilayer perceptron neural network. The evaluation of the prediction is calculated with the mean absolute error, the root mean square error, the correlation coefficient and the index of agreement. The results show the importance of meteorological variables in the prediction of the concentration of the pollutants SO2 and PM10 in the city of Salamanca, Gto., Mexico. The results show that the proposed model perform better than multivariate linear regression and multilayer perceptron neural network. The models implemented for each monitoring booth have the ability to make predictions of air quality that can be used in a system of real-time forecasting and human health impact analysis. Among the main results of the development of this thesis we can cite: A model based on artificial neural network combined with clustering algorithms for prediction with a hour ahead of the concentration of each pollutant (SO2 and PM10) is proposed. A different model was designed for each pollutant and for each of the three monitoring booths of the REDMAS. A model to predict the average of pollutant concentration in the next 24 hours of pollutants SO2 and PM10 is proposed, based on artificial neural network combined with clustering algorithms. Model was designed for each booth of the REDMAS and each pollutant separately. Resumen La contaminación atmosférica es una amenaza aguda, constituye un fenómeno que tiene particular incidencia sobre la salud del hombre. Los cambios que se producen en la composición química de la atmósfera pueden cambiar el clima, producir lluvia ácida o destruir el ozono, fenómenos todos ellos de una gran importancia global. La Organización Mundial de la Salud (OMS) considera la contaminación atmosférica como una de las más importantes prioridades mundiales. Salamanca, Gto., México; ha sido catalogada como una de las ciudades más contaminadas en este país. La industria de la zona propició un importante desarrollo económico y un crecimiento acelerado de la población en la segunda mitad del siglo XX. Las afectaciones en el aire son graves y se han hecho importantes esfuerzos por medir las concentraciones de los contaminantes. Las principales fuentes de contaminación son fuentes fijas como industrias químicas y de generación eléctrica. Los contaminantes que se han registrado como preocupantes son el Bióxido de Azufre (SO2) y las Partículas Menores a 10 micrómetros (PM10). La predicción de las concentraciones de estos contaminantes puede ser una potente herramienta que permita tomar medidas preventivas como reducción de emisiones a la atmósfera y alertar a la población afectada. En la presente tesis doctoral se propone un modelo de predicción de concentraci ón de los contaminantes más críticos SO2 y PM10 para cada caseta de monitorización de la Red de Monitorización Atmosférica de Salamanca (REDMAS). Los modelos propuestos plantean el uso de las variables meteorol ógicas como factores que influyen en la concentración de los contaminantes. La información utilizada durante el desarrollo de este trabajo corresponde a datos reales obtenidos de la REDMAS. En el Modelo Propuesto (MP) se aplican Redes Neuronales Artificiales (RNA) combinadas con algoritmos de agrupamiento. La RNA utilizada es el Perceptrón Multicapa con una capa oculta, utilizando estructuras independientes para la predicción de cada contaminante. Las variables meteorológicas disponibles para realizar la predicción fueron: Dirección de Viento (DV), Velocidad de Viento (VV), Temperatura (T) y Humedad Relativa (HR). Los algoritmos de agrupamiento K-means y Fuzzy C-means son utilizados para encontrar relaciones existentes entre los contaminantes atmosféricos en estudio y las variables meteorológicas. Dichas relaciones aportan información a las RNA para obtener la predicción de los contaminantes, la cual es agregada como entrada de las RNA. Los resultados del modelo propuesto en este trabajo son comparados con los resultados de una Regresión Lineal Multivariable (RLM) y un Perceptrón Multicapa (MLP). La evaluación de la predicción se realiza con el Error Medio Absoluto, la Raíz del Error Cuadrático Medio, el coeficiente de correlación y el índice de acuerdo. Los resultados obtenidos muestran la importancia de las variables meteorológicas en la predicción de la concentración de los contaminantes SO2 y PM10 en la ciudad de Salamanca, Gto., México. Los resultados muestran que el MP predice mejor la concentración de los contaminantes SO2 y PM10 que los modelos RLM y MLP. Los modelos implementados para cada caseta de monitorizaci ón tienen la capacidad para realizar predicciones de calidad del aire, estos modelos pueden ser implementados en un sistema que permita realizar la predicción en tiempo real y analizar el impacto en la salud de la población. Entre los principales resultados obtenidos del desarrollo de esta tesis podemos citar: Se propone un modelo basado en una red neuronal artificial combinado con algoritmos de agrupamiento para la predicción con una hora de anticipaci ón de la concentración de cada contaminante (SO2 y PM10). Se diseñó un modelo diferente para cada contaminante y para cada una de las tres casetas de monitorización de la REDMAS. Se propone un modelo de predicción del promedio de la concentración de las próximas 24 horas de los contaminantes SO2 y PM10, basado en una red neuronal artificial combinado con algoritmos de agrupamiento. Se diseñó un modelo para cada caseta de monitorización de la REDMAS y para cada contaminante por separado.

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO2) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO2 concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.