El impacto de la contaminación del aire es un tema crítico para el medioambiente y el clima. Una mala calidad del aire es un tema de importancia para la salud pública, especialmente en ambientes urbanos. El material particulado (PM), el ozono (O3) y el dióxido de nitrógeno (NO2) son los contaminantes más problemáticos en Europa y España. La Comisión Europea ha mostrado una gran preocupación por desarrollar técnicas que permitan incrementar el conocimiento sobre la dinámica de los contaminantes atmosféricos para asegurar el cumplimiento de la legislación y para informar a la población acerca de sus niveles. Además, la directiva europea 2008/50/CE establece la posibilidad de usar técnicas de modelización para informar sobre calidad del aire. Esta tesis doctoral está desarrollada en el marco de dos proyectos: El proyecto CALIOPE y el proyecto CICYT CGL2006-08903, ambos basados en la necesidad de desarrollar un sistema de calidad del aire que permita informar y entender los niveles de contaminación en Europa y España, con el objetivo de obtener un preciso pronóstico de la calidad del aire. Con ese propósito, el sistema de modelización CALIOPE se ha desarrollado con alta resolución espacial y temporal sobre Europa (12 km x 12 km y 15 capas, 1 hora), dominio madre, y España (4 km x 4 km y 15 capas, 1 hora), dominio anidado. CALIOPE consiste en un conjunto de modelos que tienen en cuenta la contaminación tanto antropogénica como natural. La disponibilidad del supercomputador MareNostrum, alojado en el Barcelona Supercomputer Center- Centro Nacional de Supercomputación, ha permitido trabajar a tan alta resolución. El objetivo principal de esta tesis es aumentar la confianza científica en el sistema CALIOPE, identificando sus puntos fuertes y débiles con un nivel de detalle que contribuya a establecer necesidades de mejora en el proceso de modelización. Por tanto, el presente trabajo ha evaluado espacial y temporalmente las simulaciones de calidad del aire sobre Europa y España en términos de O3, NO2, SO2, PM2.5 y PM10 en superficie sobre el año completo 2004. Para identificar el origen de las incertidumbres en la modelización del PM, su composición química ha sido también evaluada en ambos dominios. Las evaluaciones han sido realizadas sobre más de 150 estaciones de calidad del aire (más de 2 millones de datos experimentales). Además, esta tesis ha usado el sistema CALIOPE para analizar los patrones de calidad del aire sobre 2004, identificando claramente las áreas de contaminación. Las ideas más importantes que se desprenden de esta tesis son tres. Primero, las condiciones de contorno químicas basadas en un modelo global, como el LMDz-INCA2, son esenciales para modelizar el O3 troposférico sobre los dominios de estudio. Segundo, para simular la concentración de PM en el sur de Europa, tanto a escala rural como urbana, la contribución de polvo procedente del desierto del Sahara deber ser considerada debido a la proximidad al continente africano. La contribución del polvo del desierto a través del modelo BSC-DREAM8b ayuda satisfactoriamente a modelizar los picos de PM10 observados. Tercero, para ser capaz de modelizar la calidad del aire a escala urbana sobre España es esencial (1) una alta resolución espacial y temporal que permita describir fenómenos mesoescalares en áreas de topografía compleja , (2) un modelo de emisiones altamente desagregado como HERMES; (3) unos modelos que representen el estado actual del conocimiento en meteorología y química atmosférica / The impact of air pollution is a critical topic in environment and climate. Poor air quality is an important public health issue, especially in urban environments. Particulate matter (PM), tropospheric ozone (O3) and nitrogen dioxide (NO2) are the main problematic pollutants in Europe and Spain. The European Commission has shown a great concern for developing actions that allow increasing the knowledge on dynamics of atmospheric pollutants to assure the accomplishment of legislation and to inform the population about their levels. The European directive 2008/50/EC establishes the possibility of using modelling techniques to assess air quality. This Ph.D. thesis is developed in the framework of two projects: the CALIOPE project and the CGL2006-08903 CICYT project, both based on the necessity to develop an air quality modelling system that allows assessing and understanding the air pollution levels in Europe and Spain, with the aim of obtaining a precise air quality forecast. For that purpose, the CALIOPE air quality modelling system has been developed with high spatial and temporal resolution over Europe (12 km x 12 km, 1 h), as a mother domain; and Spain (4 km x 4 km, 1 h), as the nested domain. The CALIOPE system consists in a set of models that take into account both anthropogenic and natural pollution. The availability of the MareNostrum supercomputer, held in Barcelona Supercomputing Center- Centro Nacional de Supercomputación, has allowed such configuration of the CALIOPE system. The main objective of the present Ph.D. thesis is to increase the scientific confidence on the CALIOPE system, identifying skills and weakness with a degree of detail that contributes to establish necessities of improvements in the modelling process. Therefore, the present work has spatially and temporally evaluated CALIOPE air quality simulations over Europe and Spain in terms of O3, NO2, SO2, PM2.5, PM10 concentrations over the full year 2004. In order to identify the origin of uncertainties in PM modelling, PM chemical composition has been also evaluated in both target domains. Evaluations have been performed across more than 150 air quality-monitoring stations and over more than 2 million of experimental data. Furthermore, this Ph.D. thesis has used the CALIOPE system to assess air quality pattern over the year 2004, identifying clearly the areas of air pollution. There are three major thrusts of the present Ph.D. thesis. First, chemical boundary condition based on a global model, such as LMDz-INCA2, becomes essential to model O3 background concentrations in the target domains. Second, to simulate PM concentration in southern Europe, both regional and urban scales, the contribution of dust from the Saharan desert should be taken into account, since that region is frequently affected by dust outbreaks due to its proximity to the African continent. The contribution of desert dust through the BSC-DREAM8b helps to satisfactory model the observed episodic PM10 concentration peaks. Even more, the contribution of sea-salt aerosol is especially important over coastal areas. Third, to be able to model the air quality in urban scale over Spain it is essential (1) a high spatial (4 km x 4 km and 15 layers) and temporal (1h) resolution that allows describing mesoscale phenomena in very complex terrains; (2) a high disaggregated emission model to describe the sources, such as HERMES; and (3) an state-of-the-science meteorological and chemical models. This Ph.D. thesis has demonstrated that CALIOPE system applied over Europe and Spain is a useful tool which may contribute to (1) forecast air pollution in urban/suburban areas with a pervasive influence of anthropogenic emissions on a local scale and over very complex terrains and meteorology patterns; (2) assess about air pollution, discriminating between anthropogenic and natural episodes; and (3) manage air pollution, by means of modification of urban strategies or requirements of the legislation.

Anthropogenic emissions into the troposphere can impact air quality, leading to poorer health outcomes in the affected areas. Volatile organic compounds (VOCs) are a group of chemical compounds, including some which are toxic, that are precursors in the formation of ground-level ozone and secondary organic aerosols. VOCs have a variety of sources, and the distribution of atmospheric VOCs differs significantly over time and space. Historically, the large number of chemical species present at low concentrations (parts-per-trillion to parts-per-billion by volume) have made VOCs difficult to measure in ambient air. However, with improvements in analytical instrumentation, these measurements are becoming more common place. Direct mass spectrometry (MS), such as membrane introduction mass spectrometry (MIMS) and proton-transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) facilitate real-time, continuous measurements of VOCs in air, with full scan mass spectral data capturing changes in chemical composition with high temporal resolution. Operated on-road, mobilized direct MS has been used for quantitative mapping of VOCs at the neighborhood scale, but identifying VOC sources based on the observed mixture of molecules in the full scan MS dataset has yet to be explored. This dissertation describes the use of chemometric techniques to interrogate full scan MS data, and the progression from discriminating VOC samples of known chemical composition based on full scan MIMS data through to the apportionment of VOC sources measured continuously with a PTR-ToF-MS system operating in a moving vehicle. Lab‐constructed VOC samples of known chemical composition and concentration demonstrated the use of principal component analysis (PCA) to discriminate, and k-nearest neighbours to classify, samples based on normalized full scan MIMS data. Furthermore, multivariate curve resolution-alternating least squares (MCR-ALS) was used to resolve mixtures into molecular component contributions. PCA was also used to discriminate ‘real-world’ VOC mixtures (e.g., woodsmoke VOCs, headspace above aqueous hydrocarbon samples) of unknown chemical composition measured by MIMS. Using vehicle mounted MIMS and PTR-ToF-MS systems, full scan MS data of ambient atmospheric VOCs were collected and PCA was applied to the normalized full scan MS data. A supervised analysis performed PCA on samples collected near known VOC sources, while an unsupervised analysis using PCA followed by cluster analysis was used to identify groups in a continuous, time series PTR-ToF-MS dataset measured between Nanaimo and Crofton, British Columbia (BC). In both the supervised and unsupervised analysis, samples impacted by emissions from different sources (e.g., internal combustion engines, sawmills, composting facilities, pulp mills) were discriminated. With PCA, samples were discriminated based on differences in the observed full scan MS data, however real-world samples are often impacted by multiple VOC sources. MCR-weighted ALS (MCR-WALS) was applied to the continuous, time series PTR-ToF-MS data from three field campaigns on Vancouver Island, BC for source apportionment. Variable selection based on signal-to-noise ratios was used to reduce the mass list while retaining the observed m/z that capture changes in the mixture of VOCs measured, improving model results, and reducing computation time. Both point (e.g., anthropogenic hydrocarbon emissions, pulp mill emissions) and diffuse (e.g., VOCs from forest fire smoke) VOC sources were identified in the data, and were apportioned to determine their contributions to the measured samples. The data analyzed captured fine scale changes in the ambient VOCs present in the air, and geospatial maps of each individual source, and of the source apportionment were used to visualize the distribution of VOC sources across the sampling area. This work represents the first use of MCR-WALS to identify and apportion ambient VOC sources based on continuous PTR-ToF-MS data measured from a moving vehicle. The methods described can be applied to larger scale field campaigns for the source apportionment of VOCs across multiple days to capture diurnal and seasonal variations. Identifying spatial and temporal trends in the sources of VOCs at the regional scale can help to identify pollution ‘hot spots’ and inform evidence-based public policy for improving air quality. / Graduate / 2022-08-17