A Comparison of Clustering Techniques for Meteorological Analysis

Present work proposes the application of several clustering techniques (k-means, SOM k-means, k-medoids, and agglomerative hierarchical) to analyze the climatological conditions in different places. To do so, real-life data from data acquisition stations in Spain are analyzed, provided by AEMET (Spanish Meteorological Agency). Some of the main meteorological variables daily acquired by these stations are studied in order to analyse the variability of the environmental conditions in the selected places. Additionally, it is intended to characterize the stations according to their location, which could be applied for any other station. A comprehensive analysis of four different clustering techniques is performed, giving interesting results for a meteorological analysis

Vertical wind profile characterization and identification of patterns based on a shape clustering algorithm

Wind power plants are becoming a generally accepted resource in the generation mix of many utilities. At the same time, the size and the power rating of individual wind turbines have increased considerably. Under these circumstances, the sector is increasingly demanding an accurate characterization of vertical wind speed profiles to estimate properly the incoming wind speed at the rotor swept area and, consequently, assess the potential for a wind power plant site. The present paper describes a shape-based clustering characterization and visualization of real vertical wind speed data. The proposed solution allows us to identify the most likely vertical wind speed patterns for a specific location based on real wind speed measurements. Moreover, this clustering approach also provides characterization and classification of such vertical wind profiles. This solution is highly suitable for a large amount of data collected by remote sensing equipment, where wind speed values at different heights within the rotor swept area are available for subsequent analysis. The methodology is based on z-normalization, shape-based distance metric solution and the Ward-hierarchical clustering method. Real vertical wind speed profile data corresponding to a Spanish wind power plant and collected by using a commercialWindcube equipment during several months are used to assess the proposed characterization and clustering process, involving more than 100000 wind speed data values. All analyses have been implemented using open-source R-software. From the results, at least four different vertical wind speed patterns are identified to characterize properly over 90% of the collected wind speed data along the day. Therefore, alternative analytical function criteria should be subsequently proposed for vertical wind speed characterization purposes.The authors are grateful for the financial support from the Spanish Ministry of the Economy and Competitiveness and the European Union —ENE2016-78214-C2-2-R—and the Spanish Education, Culture and Sport Ministry —FPU16/042

Characterization of atmospheric pollution dynamics in Spain by means of air quality modelling

Atmospheric pollution causes large impacts on human health and societal economic interests and it is a threat for the ecosystems and the climate of the Earth. Improving the understanding of pollution dynamics is necessary to desing efficient air quality strategies that reduce the impacts of air pollution. This Ph.D. Thesis identifies the typical atmospheric conditions at synoptic scale that affect the Iberian Peninsula (IP) and uses them to explain the dynamics of the most relevant gaseous pollutants in Spain (nitrogen dioxide NO2, sulphur dioxide SO2, and ozone O3) by means of air quality modelling. Circulation type classifications (CTC) summarise the continuum of atmospheric circulation into a discrete number of typical circulation types (CTs). For the 1983-2012 climatic period, a CTC is derived to be useful in the characterization of air quality dynamics over the IP. Sensitivity tests to classification techniques (principal components, correlation analysis, clustering) and other factors affecting the CTC (temporal and spatial resolution, domain size, etc.) are performed to objectivize the choice of the automatic set-up that maximizes its quality. The six identified CTs -described in terms of frequency, persistence, transitions, and location of pressure systems- are consistent with CTs found in the literature. The temporal stability of the CTC, evaluated following a cross-validation process that compares the results of the climatic and yearly CTs, leads to the identification of a representative year (2012). A representative day for each CT in 2012 is identified using an objective score that minimizes the differences of the daily and the average surface pressure CT grid. The study of NO2, SO2, and O3 dynamics performed on the representative day of each CT focuses on the biggest Spanish urban areas (Madrid and Barcelona) and heavy industrial/electricity-generation areas such as Asturias (northern Spain) and the Algeciras bay (southern Spain). The state-of-the-art CALIOPE Air Quality Forecast System (CALIOPE-AQFS) that provides high-resolution data on emissions, meteorology, and pollutant concentration over Spain is the main tool used in the characterisation of pollution dynamics. The modelling system is also used to quantify the contribution of specific sources of pollutants -coal-fired power plants and on-road transport- by means of a brute-force approach and an emission-based source apportionment, respectively. The CTs control the transport patterns of SO2/NO2/O3 in Spanish continental and Atlantic areas, whereas in Mediterranean coastal areas and over complex-terrains a combination of synoptic and mesoscale dynamics (sea-land and mountain-valley breezes) explains the pollutant concentration patterns. The power plants' contribution to surface concentration (up to 55 µgSO2 m-3 and 32 µgNO2 m-3) occurs mainly close to the source (< 20 km) related to vertical diffusion when the emission is injected within the planetary boundary layer. However, the SO2/NO2 plumes can reach distances higher than 250 km. The daily maximum O3 concentration attributed to the on-road transport emissions from Madrid and Barcelona contribute up to 24% and 8% to total O3 concentration, respectively, but it is particularly significant (up to 80-100 µg m-3 in an hour) to the O3 concentration peak during the central hours of the day in April-September. The long-range transport of O3 to the IP is controlled by the CTs and its concentration is very significant in the area of influence of Madrid and Barcelona, particularly under cold CTs (70-96%). This Ph.D. Thesis has proven that CALIOPE-AQFS (1) is useful to characterise the 3-D dynamics of primary and secondary pollutants in Spain under typical CTs; (2) is able to attribute and quantify air pollution to its sources via brute force and source apportionment; and (3) has the potential to help in the design of specific, science-based abatement strategies that minimize air pollution impacts.La contaminación atmosférica genera perjuicios en la salud humana, en los intereses económicos de la sociedad y constituye una amenaza para los ecosistemas y el clima de la Tierra. Avanzar en la comprensión de la dinámica de la contaminación facilita el diseño de estrategias de calidad del aire que reduzcan sus impactos. Esta Tesis Doctoral identifica objetivamente patrones típicos de circulación atmosférica (PT) que afectan a la Península Ibérica (PI) a escala sinóptica para explicar la dinámica de los principales contaminantes gaseosos en España (dióxido de nitrógeno NO2, dióxido de azufre SO2 y ozono O3) mediante modelización de la calidad del aire. Las clasificaciones sinópticas (CS) discretizan el continuo de la circulación atmosférica en un catálogo de PT. Para el período climático 1983-2012, se establece una CS útil para el estudio de la dinámica de la contaminación atmosférica en la PI. Tests de sensibilidad para técnicas automáticas de clasificación (análisis de componentes principales, de correlación y clustering) y para otros factores que afectan a la CS (resolución temporal y espacial, tamaño del dominio, etc.) objetivizan la elección de la configuración que maximiza su calidad. Los seis PT identificados - descritos en términos de frecuencia, persistencia, transiciones y ubicación de los sistemas de presión - son consistentes con la literatura. La evaluación de la estabilidad temporal de la clasificación, mediante un proceso de validación cruzada que compara los PT climáticos con PT identificados en CS anuales, permite identificar un año representativo (2012). Un día representativo de cada PT es elegido gracias a un algoritmo que minimiza las diferencias de la malla de presiones diaria respecto de la del PT promedio. El estudio de la dinámica de NO2, SO2 y O3 se realiza en el día representativo de cada PT focalizando en las principales áreas urbanas de España (Madrid y Barcelona) y en importantes áreas industriales y/o de generación eléctrica (Asturias, bahía de Algeciras). El sistema de CALIdad del aire OPeracional para España (CALIOPE) que proporciona datos de alta resolución sobre emisiones, meteorología y concentración de contaminantes es la principal herramienta utilizada en el estudio. CALIOPE permite cuantificar la contribución de determinadas fuentes de emisión, centrales térmicas de carbón y transporte rodado, mediante un enfoque de fuerza bruta y de asignación de fuentes, respectivamente. Los PT controlan el transporte de SO2/NO2/O3 en áreas atlánticas y continentales de España mientras que en zonas costeras mediterráneas y/o de topografía compleja, una combinación de procesos sinópticos y de mesoescala (brisas marinas y de valle) explica los patrones de contaminación. La contribución de SO2 y NO2 de las centrales térmicas a la concentración en superficie (hasta 55 µg m-3 y 32 µg m-3, respectivamente) se produce principalmente cerca de la fuente (<20 km) por difusión vertical de la emisión cuando ésta se inyecta en la capa límite planetaria. Sin embargo, los penachos de SO2/NO2 pueden alcanzar distancias superiores a los 250 km. La contribución máxima diaria de O3 atribuido a emisiones del transporte rodado de Madrid y Barcelona alcanza el 24% y el 8%, respectivamente pero es particularmente significativa (hasta 80-100 µg m-3 en una hora) a mediodía durante el pico de concentración de O3. El transporte a larga distancia de O3 hacia la PI es controlado por los PT y su contribución es muy importante en el área de influencia de Madrid y Barcelona, en particular bajo los PT fríos (70-96%). Esta Tesis Doctoral ha demostrado que CALIOPE es (1) útil para caracterizar la dinámica 3-D de contaminantes primarios y secundarios en España bajo diferentes PT; (2) capaz de atribuir y cuantificar la contaminación a sus fuentes a través de fuerza bruta y atribución de fuentes; y (3) potencialmente útil en el diseño de estrategias de mitigación específicas que minimicen los impactos de la contaminación atmosférica.Postprint (published version

Geohealth. A Geographic Information System for clinical research

Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceThe objective of the project has been the development of a system for clinical, epidemiological, and translational research capable of associating environmental variables and geospatial information with clinical patient’s data. The system aims to empower clinical researchers with a system that helps improve the generation of more meaningful and applicable results that directly benefit human health. The system has integrated pollution, pollen, and meteorological data as well as demographic information of the region of Andalusia, Spain. The heterogeneous data comes from different sources such as the Meteorological Spanish Agency (AEMET), the Spanish Ministry for the Ecological Transition, and the Demographic challenge or the National Institute of Statistics (INE). The project includes three main deliverables: the development of a system for clinical, epidemiological, and translational research, a geodemographic segmentation, and an air quality characterization. The system, called “Geohealth”, includes a module for the observation of all the data on a single map. This module allows researchers to observe and understand the geographical distribution of patients, the demographic information of the census sections, as well as the time series of the meteorological, pollution, and pollen data. In addition, a second module called “Segmentations”, includes the results of the first study developed for this project which aimed at discovering and understanding which are the characteristics of the different clusters of census sections among the province of Seville (Spain) through the development of two geodemographic segmentations. A second study, based on the pollution times series data, has been developed and integrated into the system. The pollution time series have been processed and the different values, measured by the pollution stations, have been interpolated for the whole territory. Once each census section has assigned the values for each pollutant, they have been transformed into the Air Quality Health Index (AQHI) scale, developed by the Canadian government, which allows understanding the impact of the combination of the pollutant on health. The system has been evaluated in collaboration with the Allergology department of the Virgen Macarena Hospital, with a dataset of asthmatic patients that have attended emergency care due to an asthma attack during the years between 2014 and 2019

Self-Organizing Maps to Validate Anti-Pollution Policies

This study presents the application of self-organizing maps to air-quality data in order to analyze episodes of high pollution in Madrid (Spain’s capital city). The goal of this work is to explore the dataset and then compare several scenarios with similar atmospheric conditions (periods of high Nitrogen dioxide concentration): some of them when no actions were taken and some when traffic restrictions were imposed. The levels of main pollutants, recorded at these stations for eleven days at four different times from 2015 to 2018, are analyzed in order to determine the effectiveness of the anti-pollution measures. The visualization of trajectories on the self-organizing map let us clearly see the evolution of pollution levels and consequently evaluate the effectiveness of the taken measures, after and during the protocol activation time