Niveles, composición y origen del material particulado atmosférico en los sectores Norte y Este de la Península Ibérica y Canarias

Tesis del Departament de Geoquímica, Petrologia i Prospecció Geològica de la Universitat de Barcelona (UB).-- Fecha de defensa 17-12-2003.El creciente interés existente en la actualidad por la investigación en el campo del material particulado atmosférico se debe a la identificación de efectos adversos de este contaminante sobre la salud y los ecosistemas. El principal objetivo de este trabajo de investigación es evaluar los niveles, composición y origen del material particulado atmosférico en tres zonas seleccionadas de España: el País Vasco, el sector mediterráneo (Cataluña y Valencia) y Canarias. Para ello, se pretende obtener una visión de los procesos y las fuentes que regulan los niveles de material particulado a escala sinóptica y en la meso-escala, así como de las fuentes específicas con repercusión sobre los niveles y composición química del material particulado a escala local. Con estos fines se diseñó un proyecto basado en: a) la interpretación de series antiguas (1996-2000) de niveles de PST y PM10, y b) la interpretación y caracterización química de series temporales de niveles de PM10, PM2.5 y PM1 durante 2001. Los resultados obtenidos por medio de la interpretación de las series antiguas y modernas de material particulado atmosférico se contrastaron con mapas de aerosoles, imágenes de satélite y modelos de predicción de los niveles en superficie y espesor óptico de material particulado, sulfatos y materia carbonosa.A través de la interpretación de series temporales antiguas y modernas de niveles de material particulado atmosférico se logra identificar los principales procesos naturales y antropogénicos que dan lugar a episodios con altos y bajos niveles de material particulado atmosférico. A escala sinóptica y en la meso-escala estos procesos son: 1. Intrusiones de masas de aire africano 2. Advección de masas de aire atlántico 3. Circulación regional de masas de aire 4. Advección de masas de aire de origen europeoA escala local, los principales episodios de partículas tienen su origen en las emisiones ligadas a la actividad industrial o del tráfico. Se aportan datos cuantitativos para cada estación. Los resultados obtenidos acerca de la composición química del material particulado se interpretan siguiendo dos enfoques distintos: por medio del análisis químico de los principales componentes del material particulado atmosférico (materia mineral, materia carbonosa [OM+EC], compuestos inorgánicos secundarios [CIS] y aerosol marino), y aplicando un análisis estadístico de contribución de fuentes mediante un modelo receptor.Para finalizar este análisis se han comparado los resultados obtenidos con trabajos realizados en otros 6 Estados Miembros de la Unión Europea en los que se ha aplicado una metodología similar. Las concentraciones de componentes de origen típicamente antropogénico (materia carbonosa y compuestos inorgánicos secundarios) en dichos estudios europeos son análogos a los obtenidos en el presente trabajo. Sin embargo, los niveles de materia mineral son marcadamente superiores en las estaciones en España, y ello es debido principalmente a tres factores: a) la incidencia de episodios de intrusión de masas de aire africano con elevada carga particulada mineral; b) la mayor aridez de los suelos que favorece la mayor resuspensión; y c) la menor tasa de precipitación anual, que impide el lavado del material particulado depositado sobre las vías de tránsito (por erosión del firme de rodadura) y que por tanto es susceptible a volver a entrar en suspensión. Consecuentemente, no sólo es el fondo mineral en España más elevado, sino que existe también una causa antropogénica que contribuye a elevar los niveles de materia mineral en suspensión.Peer reviewe

How to effectively use interactivity to improve visual analysis in groups of novices or experts

This study contributes with a methodology to evaluate the differences between different groups of individuals, using a prototype with different interactive visualizations, created with the Shiny package, using 6 quantitative and qualitative metrics for the validation. Using an ANOVA single factor test only 1 of the 6 variables showed statistically significant differences between both groups: the engagement. This means that this is the only metric where results can be improved in order to close the gap between the group of experts and novices. The heatmap and the bar chart were considered the best visualizations for both groups, and the worst were the choropleth map and the stacked bar chart. Regarding the interactive component, the select box was a better option for the group of novices and the radio box for the group of experts. Using this study, organizations will be able to create visualizations that are suitable for different audiences

A comparative study of calibration methods for low-cost ozone sensors in IoT platforms

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper shows the result of the calibration process of an Internet of Things platform for the measurement of tropospheric ozone (O 3 ). This platform, formed by 60 nodes, deployed in Italy, Spain, and Austria, consisted of 140 metal–oxide O 3 sensors, 25 electro-chemical O 3 sensors, 25 electro-chemical NO 2 sensors, and 60 temperature and relative humidity sensors. As ozone is a seasonal pollutant, which appears in summer in Europe, the biggest challenge is to calibrate the sensors in a short period of time. In this paper, we compare four calibration methods in the presence of a large dataset for model training and we also study the impact of a limited training dataset on the long-range predictions. We show that the difficulty in calibrating these sensor technologies in a real deployment is mainly due to the bias produced by the different environmental conditions found in the prediction with respect to those found in the data training phase.Peer ReviewedPostprint (author's final draft

How to effectively use interactivity to improve visual analysis and communication in groups of novices or experts

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceConseguir passar um ponto de vista claro através da visualização de dados é um dos principais objetivos das organizações dos dias de hoje. O principal objetivo deste projeto foi perceber qual a melhor maneira de utilizar interatividade em diferentes tipos de indivíduos, especialistas e novatos, e descobrir as principais diferenças entre os dois grupos. Isto foi feito através da criação de um protótipo com diversas visualizações interativas, onde em cada uma delas foram utilizadas diferentes técnicas de visualização e interatividade. Após a sua criação, seguiu-se a validação de cada uma delas, de modo a chegar a conclusões sobre os melhores métodos a utilizar para melhorar a análise e comunicação da informação, para os diferentes grupos de indivíduos. O desenvolvimento do protótipo foi realizado com o software R, mais especificamente o pacote Shiny. O estudo contribuiu com uma metodologia para avaliar as diferenças entre grupos de especialistas e de novatos, relativamente ao protótipo de visualização que foi validado recorrendo a 6 medidas quantitativas e qualitativas. Utilizando um teste ANOVA de fator único foi possível concluir que em relação às medidas quantitativas não foram encontradas diferenças com significância estatística e em relação às medidas qualitativas a única medida que mostrou diferenças com significância estatística entre ambos os grupos foi o nível de interação (engagement). Isto significa que esta é a única métrica possível de melhorar para diminuir as diferenças entre ambos os grupos. Em relação às visualizações ambos os grupos, concordaram que as melhores foram o mapa de calor (heatmap) e o gráfico de barras e as piores visualizações foram o mapa coropleto e o gráfico de barras empilhadas. Houve, no entanto, diferenças entre a forma como os diferentes grupos interagiram com os componentes. Por exemplo, a select box foi uma melhor opção para o grupo de novatos, enquanto que a radio box foi a melhor para o grupo de especialistas. Os tooltips e o slider foram adequados para os dois tipos de indivíduos. Também foi comprovado que o pacote Shiny é uma ferramenta capaz de criar visualizações interativas eficazes para diferentes tipos de indivíduos uma vez que, em média, os participantes obtiveram ótimos resultados utilizando medidas qualitativas ou quantitativas. Os resultados deste estudo, permitirão às organizações a adaptação eficiente das suas visualizações a diferentes tipos de audiência.Getting a clear point of view through data visualization is one of the main goals of todays’ organizations. The main objective of this project was to understand the most efficient way to use interactivity in different groups of individuals, experts and novices, and to discover the main differences between these two groups. This was achieved through the creation of a prototype with several interactive visualizations, where in each of them different visualizations and interaction techniques were used. After the creation of the prototype, the next step was the validation of each one of them to reach conclusions on what are the most effective means to improve visual analysis and communication, in different groups of individuals. The development of the prototype was done using the R software, and most specifically the Shiny package. This study contributed with a methodology to evaluate the differences between experts and novices, using the visualization prototype that was validated with 6 quantitative and qualitative metrics. Using an ANOVA single factor test it was possible to conclude that regarding the quantitative measures no statistically significant differences were found. However, regarding the qualitative measures the only measure that had statistically significant differences between both groups was the engagement measure. This means that this is the only metric where results can be improved in order to close the gap between the group of experts and novices. Regarding the visualizations, both groups agreed that the best visualizations were the heatmap and the bar chart and the worst visualizations were the choropleth map and the stacked bar chart. Nevertheless, there were differences between how the different groups interacted with the components. For example, the select box was a better option for the novice’s group, while the radio box was the best for the expert’s group. The tooltips and the slider are adequate for both types of individuals. It was also proved that the Shiny package is a tool that is capable of creating effective interactive visualizations for different types of individuals, since that on average the participants obtained great results using qualitative or quantitative measures. The results of this study will allow organizations to efficiently adapt their visualizations to different types of audiences

Study of the morning transition of the atmospheric boundary layer

Póster presentado en: European Geosciences Union General Assembly celebrado del 19-24 de abril de 2009 en Viena.This research has been funded by the Spanish Ministry of Education and Science (projects CGL2004-03109 and CGL2006-12474-C03-03. IV PRICIT program (supported by CM and UCM) has also partially financed this work through the Research Group “Micrometeorology and Climate Variability” (nº 910437)

Toward a Standardised Thermal-Optical Protocol for Measuring Atmospheric Organic and Elemental Carbon: The EUSAAR Protocol

Thermal-optical analysis is a conventional method for determining the carbonaceous aerosol fraction and for classifying it into organic carbon, OC, and elemental carbon, EC. Unfortunately, the different thermal evolution protocols in use can result in a wide elemental carbon-to-total carbon variation by up to a factor of five. In Europe, there is currently no standard procedure for determining the carbonaceous aerosol fraction which implies that data from different laboratories at various sites are of unknown accuracy and cannot be considered comparable. In the framework of the EU-project EUSAAR (European Supersites for Atmospheric Aerosol Research), a comprehensive study has been carried out to identify the causes of differences in the EC measured using different thermal evolution protocols; thereby the major positive and negative biases affecting thermal-optical analysis have been isolated and minimised to define an optimised protocol suitable for European aerosols. Our approach to improve the accuracy of the discrimination between OC and EC was essentially based on four goals. Firstly, charring corrections rely on faulty assumptions ¿e.g. pyrolytic carbon is considered to evolve completely before native EC throughout the analysis¿, thus we have reduced pyrolysis to a minimum by favoring volatilisation of OC. Secondly, we have minimised the potential negative bias in EC determination due to early evolution of light absorbing carbon species at higher temperatures in the He-mode, including both native EC and combinations of native EC and pyrolytic carbon potentially with different specific cross section values. Thirdly, we have minimised the potential positive bias in EC determination resulting from the incomplete evolution of OC during the He-mode which then evolves during the He/O2-mode, potentially after the split point. Finally, we have minimised the uncertainty due to the position of the OC/EC split point on the FID response profile by introducing multiple desorption steps in the He/O2-mode. Based on different types of carbonaceous PM encountered across Europe, we have defined an optimised thermal evolution protocol, the EUSAAR_2 protocol, as follows: step 1 in He, 200°C for 120s; step 2 in He 300°C for 150s; step 3 in He 450°C for 180s; step 4 in He 650°C for 180s. For steps 1-4 in He/O2, the conditions are 500°C for 120 s, 550°C for 120s, 700°C for 70s, and 850°C for 80s, respectively.JRC.DDG.H.2-Climate chang

Distributed multi-scale calibration of low-cost ozone sensors in wireless sensor networks

New advances in sensor technologies and communications in wireless sensor networks have favored the introduction of low-cost sensors for monitoring air quality applications. In this article, we present the results of the European project H2020 CAPTOR, where three testbeds with sensors were deployed to capture tropospheric ozone concentrations. One of the biggest challenges was the calibration of the sensors, as the manufacturer provides them without calibrating. Throughout the paper, we show how short-term calibration using multiple linear regression produces good calibrated data, but instead produces biases in the calculated long-term concentrations. To mitigate the bias, we propose a linear correction based on Kriging estimation of the mean and standard deviation of the long-term ozone concentrations, thus correcting the bias presented by the sensors.Peer ReviewedPostprint (published version

Multisensor data fusion calibration in IoT air pollution platforms

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This article investigates the calibration of low-cost sensors for air pollution. The sensors were deployed on three Internet of Things (IoT) platforms in Spain, Austria, and Italy during the summers of 2017, 2018, and 2019. One of the biggest challenges in the operation of an IoT platform, which has a great impact on the quality of the reported pollution values, is the calibration of the sensors in an uncontrolled environment. This calibration is performed using arrays of sensors that measure cross sensitivities and therefore compensate for both interfering contaminants and environmental conditions. This article investigates how the fusion of data taken by sensor arrays can improve the calibration process. In particular, calibration with sensor arrays, multisensor data fusion calibration with weighted averages, and multisensor data fusion calibration with machine learning models are compared. Calibration is evaluated by combining data from various sensors with linear and nonlinear regression models.This work was supported in part by the NationalSpanish funding under Grant TIN2016-78473-C3-1-R, in part by RegionalProject under Grant 2017SGR-990, in part by EU H2020 CAPTOR Project, inpart by AGAUR SGR44, in part by the Agencia Estatal de Investigación underGrant CGL2017-82093-ERC, and in part by the Spanish Ministry of Economy,Industry and Competitiveness under Grant EUIN2017-85799Peer ReviewedPostprint (author's final draft

Organic and Elemental Carbon in the Urban Background in an Eastern Mediterranean City

The Mediterranean region is an important area for air pollution as it is the crossroads between three continents; therefore, the concentrations of atmospheric aerosol particles are influenced by emissions from Africa, Asia, and Europe. Here we concentrate on an eleven-month time series of the ambient concentration of organic carbon (OC) and elemental carbon (EC) between May 2018– March 2019 in Amman, Jordan. Such a dataset is unique in Jordan. The results show that the OC and EC annual mean concentrations in PM2.5 samples were 5.9 ± 2.8 µg m–3 and 1.7 ± 1.1 µg m–3, respectively. It was found that the majority of OC and EC concentrations were within the fine particle fraction (PM2.5). During sand and dust storm (SDS) episodes OC and EC concentrations were higher than the annual means; the mean values during these periods were about 9.6 ± 3.5 µg m–3 and 2.5 ± 1.2 µg m–3 in the PM2.5 samples. Based on this, the SDS episodes were identified to be responsible for an increased carbonaceous aerosol content as well as PM2.5 and PM10 content, which may have direct implications on human health. This study encourages us to perform more extensive measurements during a longer time period and to include an advanced chemical and physical characterization for urban aerosols in the urban atmosphere of Amman, which can be representative of other urban areas in the region

Organic and Elemental Carbon in the Urban Background in an Eastern Mediterranean City

The Mediterranean region is an important area for air pollution as it is the crossroads between three continents; therefore, the concentrations of atmospheric aerosol particles are influenced by emissions from Africa, Asia, and Europe. Here we concentrate on an eleven-month time series of the ambient concentration of organic carbon (OC) and elemental carbon (EC) between May 2018–March 2019 in Amman, Jordan. Such a dataset is unique in Jordan. The results show that the OC and EC annual mean concentrations in PM2.5 samples were 5.9 ± 2.8 µg m–3 and 1.7 ± 1.1 µg m–3, respectively. It was found that the majority of OC and EC concentrations were within the fine particle fraction (PM2.5). During sand and dust storm (SDS) episodes OC and EC concentrations were higher than the annual means; the mean values during these periods were about 9.6 ± 3.5 µg m–3 and 2.5 ± 1.2 µg m–3 in the PM2.5 samples. Based on this, the SDS episodes were identified to be responsible for an increased carbonaceous aerosol content as well as PM2.5 and PM10 content, which may have direct implications on human health. This study encourages us to perform more extensive measurements during a longer time period and to include an advanced chemical and physical characterization for urban aerosols in the urban atmosphere of Amman, which can be representative of other urban areas in the region