Using Geographically Referenced Data on Environmental Exposures for Public Health Research: A Feasibility Study Based on the German Socio-Economic Panel Study (SOEP)

Background: In panel datasets information on environmental exposures is scarce. Thus, our goal was to probe the use of area-wide geographically referenced data for air pollution from an external data source in the analysis of physical health. Methods: The study population comprised SOEP respondents in 2004 merged with exposures for NO2, PM10 and O3 based on a multi-year reanalysis of the EURopean Air pollution Dispersion-Inverse Model (EURAD-IM). Apart from bivariate analyses with subjective air pollution we estimated cross-sectional multilevel regression models for physical health as assessed by the SF-12. Results: The variation of average exposure to NO2, PM10 and O3 was small with the interquartile range being less than 10µg/m3 for all pollutants. There was no correlation between subjective air pollution and average exposure to PM10 and O3, while there was a very small positive correlation between the first and NO2. Inclusion of objective air pollution in regression models did not improve the model fit. Conclusions: It is feasible to merge environmental exposures to a nationally representative panel study like the SOEP. However, in our study the spatial resolution of the specific air pollutants has been too little, yet.SOEP, Geographically Referenced Data, Feasibility Study, Air Pollution, EURAD-IM, Physical Health

Evaluation of receptor and chemical transport models for PM10 source apportionment

In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models

Four-Dimensional Variational Assimilation of Atmospheric Chemical Data - Application to Regional Modelling of Air Quality

The chemistry transport model system EURAD-IM and its variational data assimilation implementation are applied to air quality assessment problems. The facility of joint initial value and emission rate optimisation together with a nested 4d-var module is employed to the measurement campaign BERLIOZ. To emphasise the benefits of computationally efficient data assimilation for monitoring and simulating air quality, results of an operational 3d-var implementation are also given

Simulação da qualidade do ar interior em ambiente escolar

Mestrado em Engenharia do AmbienteA qualidade do ar interior (QAI) em salas de aula é um fator determinante na incidência e prevalência de doenças do foro respiratório dos utentes do espaço escolar (alunos, professores e funcionários), sendo particularmente relevante no caso de crianças e jovens. Com base neste problema, esta dissertação tem como principal objetivo avaliar qual a contribuição da poluição exterior para os níveis de QAI numa escola do concelho de Aveiro (Escola Básica nº 1 da Glória), recorrendo à aplicação do modelo IAQX (Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure). Utilizaram-se como dados de entrada no modelo IAQX as concentrações exteriores de monóxido de carbono (CO) simuladas no modelo de qualidade do ar VADIS, obtendo-se dessa forma as concentrações interiores numa das salas de aulas da escola selecionada. A comparação destas com os valores medidos possibilitou, assim, aferir qual a contribuição do ar exterior para os níveis de QAI na Escola Básica nº 1 da Glória. Os resultados obtidos nesta dissertação demonstram que as concentrações exteriores de CO têm influência nas concentrações interiores da Escola Básica nº 1 da Glória. Os valores simulados com o modelo IAQX não são totalmente concordantes com os valores medidos no interior da sala de aula, o que pode ser explicado por fatores locais, tais como o fator humano (por exemplo, a abertura de janelas), ou por fatores relacionados com o escoamento e dispersão atmosférica. No entanto, tanto os valores medidos como os valores simulados da concentração interior de CO não ultrapassam o valor máximo para edifícios escolares estipulado no Decreto-Lei nº 79/2006, de 4 de abril. Apesar dos resultados revelarem que as concentrações interiores de CO não indicam uma má QAI na Escola Básica nº 1 da Glória, para garantir que a escola esteja a cumprir todos os padrões de uma boa QAI, é necessário analisar mais poluentes e parâmetros para além do CO.The indoor air quality (IAQ) in classrooms is a key factor in the incidence and prevalence of respiratory diseases of the school users (students, teachers and staff), being particularly relevant for children and youth. Based on this problem, the main objective of this thesis is to evaluate the contribution of outdoor pollution to the IAQ levels in a school (Escola Básica nº 1 da Glória) of Aveiro town (Portugal), by applying the IAQX (Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure) model. Using as input data the carbon monoxide (CO) outdoor concentrations simulated in the air quality VADIS model, the indoor concentrations in one of the classrooms of the selected school were obtained. The comparison of these with the measured values allowed the assessment of the contribution of outdoor air for IAQ levels in Escola Básica nº 1 da Glória. The results obtained in this work show that CO outdoor concentrations have influence on the indoor concentrations of Escola Básica nº 1 da Glória. The values simulated with the IAQX model inside the school classroom are not fully consistent with the measured values, which can be explained by local factors, such as the human factor (eg. the opening of windows), or by atmospheric flow/dispersion factors. However, both measured values and simulated values of CO indoor concentration do not exceed the maximum value to school buildings stipulated in Decreto-Lei nº 79/2006 of 4th April. Although the results reveal that CO indoor concentrations do not indicate a poor IAQ in Escola Básica nº 1 da Glória, to ensure that the school is fulfilling all the standards of a good IAQ, it is necessary to analyse more pollutants and parameters in addition to CO

Four-Dimensional Variational Assimilation of Aerosol Data from In-situ and Remote Sensing Platforms

Die Assimilation von Aerosoldaten war bisher im Wesentlichen auf die Verwendung von Messungen der Gesamtmassenkonzentrationen von Partikeln bis zu einer bestimmten Größe und Messungen von optischer Tiefe beschränkt. Das Chemie-Transport-Modell EURAD-IM des Rheinischen Instituts für Umweltforschung (RIU) enhält ein hochentwickeltes vierdimensionales variationales (4D-var) Assimilationssystem für Gasphasenspezies, das nun um eine teilweise adjungierte Version des Aerosol-modells MADE erweitert wurde, um speziesaufgelöste Aerosolmessungen assimilieren zu können. Vorbereitend wurde bereits der äusserst rechenzeitaufwendige Mechanismus zur Lösung der Chemie der sekundären anorganischen Aerosole innerhalb des MADE mithilfe eines I/O-mapping-Verfahrens ersetzt. Der resultierende Algorithmus wurde nun adjungiert und die Funktionalität des adjungierten Aerosoltransportes sichergestellt. Desweiteren wurden verschiedene Beobachtungsoperatoren entwickelt und gleichzeitig adjungiert. Dazu gehören Integrationsroutinen für Massenkonzentrationen und Anzahldichten. Im Rahmen des AERO-SAM Projektes wurde ein Strahlungstransportmodell, Teil eines Satelliten-Retrieval-Systems, in das Modell eingebaut. Die Besonderheit liegt darin, dass das Modell speziesaufgelöste aerosoloptische Tiefen liefert. Das so konstruierte Aerosolassimilationssystem ist auf zwei Episoden angewandt worden. Als erstes auf den Sommer 2003, als ein langanhaltendes Hochdruckgebiet über Europa lag. Diese Wetterlage begünstigte Waldbrände und brachte stark erhöhte Feinstaubbelastung mit sich. In diesem Zeitraum wurde das neue Assimilationssystem getestet und der Nutzen der Assimilation von PM10 insbesondere von speziesaufgelösten Satellitendaten untersucht. Außerdem wurde die ZEPTER-2 Messkampagne aus dem Herbst 2008 ausgewählt. Ein zur Messplatform umgebauter Zeppelin, der mit einem CPC (Condensation Particle Counter) ausgestattet war, hat räumlich und zeitlich hochaufgelöste Partikelanzahldichten gemessen. In dieser Episode wurde der Fokus auf die Assimilation der Anzahldichten sowie der Leistung des Systems auf Modellgittern mit hoher Auflösung gerichtet. In beiden Fällen wurde Anfangswertoptimierung durchgeführt und das System selbst, sowie das Vermögen, die Vorhersage von Aerosolen zu verbessern, untersucht. Es hat sich herausgstellt, dass sich durch Assimilation von Aerosolen eine deutliche Verbesserung der Vorhersage insgesamt erzielen lässt, während durch die Assimilation speziesaufgelöster Retrievals zusätzlich die Zusammensetzung der Aerosole angepasst werden kann

Singular Vector Based Targeted Observations of Atmospheric Chemical Compounds

Measurements of the earth's environment provide only sparse snapshots of the state of the system due to their insufficient temporal and spatial density. In face of these limitations, the measurement configurations need to be optimized to get a best possible state estimate. One possibility to optimize the state estimate is provided by targeted observations of sensitive system states, where measurements are of great value for forecast improvements. In the recent years, numerical weather prediction adapted singular vector analysis with respect to initial values as a novel method to identify sensitive locations. In the present work, this technique was transferred from meteorological to chemical forecast. Besides initial values, emissions were introduced as controlling variables. Since time-variant amounts of emissions continuously act on the chemical evolution, targeting observations of emissions is a challenging task. Alternatively, uncertainties in the amplitude of the diurnal profile of emissions are analyzed, yielding emission factors as target variables. Special operators were designed to address specific questions of atmospheric chemistry, like the VOC- versus NOx-sensitivity of the ozone formation. The concept of adaptive observations was studied on two levels of complexity: At first, targeted singular vectors were implemented in a chemistry box model which only treats chemical reaction kinetics. Due to the absence of spatial dimensions, the chemistry box model only provides ranking lists of measurement priorities for different compounds. In the second step, singular vector analysis was implemented in a chemical transport model to additionally determine optimal placements of measurements. Both models have been tested and evaluated by conducting a comprehensive set of case studies. Particular questions of specific interest for the chemical system were examined, where the newly designed operators were applied. Results show large differences in sensitivities of different compounds. Consequently, an optimal measurement configuration benefits from omitting measurements of compounds of low sensitivity. It is demonstrated how targeted observations of chemical compounds depend on the considered simulation interval, meteorological conditions, and the underlying chemical composition. Accomplished studies clearly identify strong differences between meteorological and chemical target areas. These differences reveal the importance of the chemical composition and emphasize the significance of chemical singular vectors for effective campaign planing