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This Ph.D. thesis assesses the impact of the change in the hazardous classification of formaldehyde in vehicle paint shops from an environmental and economic perspective. This work includes an evaluation of compliance with the applicable emission limit value for formaldehyde, a proposal of options to reduce the emissions and their economic impact, a Life Cycle Assessment of the painting process in a real vehicle paint shop and an eco-efficiency analysis. The outcomes of this thesis allowed to make a proposal for the most eco-efficient vehicle paint shop in view of formaldehyde emissions performance.

Comprehensive monitoring of NO2 exceedances is imperative for protecting human health, especially in urban areas with traffic. However, an accurate spatial characterization of the exceedances is challenging due to the typically low density of air quality monitoring stations and the inherent uncertainties in urban air quality models. We study how observational data from different sources and timescales can be combined with a dispersion air quality model to obtain bias-corrected NO2 hourly maps at the street scale. We present a kriging-based data fusion workflow that merges dispersion model output with continuous hourly observations and uses a machine-learning-based land use regression (LUR) model constrained with past short intensive passive dosimeter campaign measurements. While the hourly observations allow the bias adjustment of the temporal variability in the dispersion model, the microscale LUR model adds information on the NO2 spatial patterns. Our method includes an uncertainty calculation based on the estimated error variance of the universal kriging technique, which is subsequently used to produce urban maps of probability of exceeding the 200¿µg¿m-3 hourly and the 40¿µg¿m-3 annual NO2 average limits. We assess the statistical performance of this approach in the city of Barcelona for the year 2019. Our results show that simply merging the monitoring stations with the model output already significantly increases the correlation coefficient (r) by +29¿% and decreases the root mean square error (RMSE) by -32¿%. When adding the time-invariant microscale LUR model in the data fusion workflow, the improvement is even more remarkable, with +46¿% and -48¿% for the r and RMSE, respectively. Our work highlights the usefulness of high-resolution spatial information in data fusion methods to better estimate exceedances at the street scale., Peer Reviewed, Postprint (published version)

Computer tomography image quality control assessment take part of Cuban national legislation, which could be difficult to accomplish for many reasons. This work is part of the set-up verifications of “in house tool” (EvaCT) designed to calculate parameters of quality control of CT images (CCCT) in various manufacturer’s phantoms, “at distance”. For this, the behavior of the established parameters was studied in 17 studies of the stablished CCCT routine with the Mediso PET/SPECT/CT Anyscan Trio equipment, comparing the results using manufacture´s reference values, and/ or the international recommended parameter´s tolerances. The results of the system were compared numerically with those obtained by the manufacturer, for each available related parameter, in the corresponding protocol, and did not show significant differences (p≥0.05). In general, the system showed a satisfactory behavior, taking as reference the values and tolerances of the manufacturer, CECMED and IAEA. The correlation between quality descriptors established with different methodologies was analyzed. The tool showed correspondence with the manufacturer's results, making available a greater number of parameters and more operational conditions to be evaluated. The mean values ±SD characterize these parameters in the equipment and its phantom, and can be used for periodic, independent and remote CCCT verification., El control de calidad de imagen de Tomografía Computada (TC) es un requisito de la normativa nacional cubana, cuyo cumplimiento se dificulta por varias razones. Este trabajo forma parte de la validación de una herramienta en desarrollo (EvaCT) diseñada para calcular parámetros de control de calidad de imágenes de TC (CCCT) en maniquíes de varios fabricantes, “a distancia”. Para ello, se estudió el comportamiento de los parámetros de control de calidad de imagen, en 17 estudios de la rutina clásica de CCCT equipo Mediso PET/SPECT/CT Anyscan Trio, y se compararon los resultados tomando como referencia los valores y las tolerancias del fabricante, y/o las recomendaciones nacionales e internacionales, según su correspondencia. Los resultados del sistema fueron confrontados numéricamente con los obtenidos por el fabricante, para cada parámetro comprable disponible, en el protocolo correspondiente, y no mostraron diferencias significativas (p≥0.05). En general, el sistema mostró un comportamiento satisfactorio. Se analizó la correlación entre descriptores de calidad establecidos con diferentes metodologías. La herramienta mostró correspondencia con los resultados del fabricante, poniendo a disposición un mayor número de parámetros y condiciones operacionales a evaluar. Conclusiones: Los valores medios ±DE, caracterizan estos parámetros en el equipo-maniquí y se pueden emplear para la verificación periódica, independiente y remota de parámetros de calidad de imagen.

Comprehensive monitoring of NO2 exceedances is imperative for protecting human health, especially in urban areas with traffic. However, an accurate spatial characterization of the exceedances is challenging due to the typically low density of air quality monitoring stations and the inherent uncertainties in urban air quality models. We study how observational data from different sources and timescales can be combined with a dispersion air quality model to obtain bias-corrected NO2 hourly maps at the street scale. We present a kriging-based data fusion workflow that merges dispersion model output with continuous hourly observations and uses a machine-learning-based land use regression (LUR) model constrained with past short intensive passive dosimeter campaign measurements. While the hourly observations allow the bias adjustment of the temporal variability in the dispersion model, the microscale LUR model adds information on the NO2 spatial patterns. Our method includes an uncertainty calculation based on the estimated error variance of the universal kriging technique, which is subsequently used to produce urban maps of probability of exceeding the 200 µg m−3 hourly and the 40 µg m−3 annual NO2 average limits. We assess the statistical performance of this approach in the city of Barcelona for the year 2019. Our results show that simply merging the monitoring stations with the model output already significantly increases the correlation coefficient (r) by +29 % and decreases the root mean square error (RMSE) by −32 %. When adding the time-invariant microscale LUR model in the data fusion workflow, the improvement is even more remarkable, with +46 % and −48 % for the r and RMSE, respectively. Our work highlights the usefulness of high-resolution spatial information in data fusion methods to better estimate exceedances at the street scale., We have received support from the Barcelona City Council through the UncertAIR project (ID 22S09501-001; Recerca Jove i emergent 2022). This research has been supported by the Ministerio de Ciencia e Innovación through the BROWNING project (grant no. RTI2018-099894-BI00), the Agencia Estatal de Investigación as part of the VITALISE project (grant no. PID2019-108086RA-I00) and the MITIGATE project (grant no. PID2020-116324RA695 I00), the H2020 Marie Skłodowska-Curie Actions (grant no. H2020-MSCA-COFUND-2016-754433), the AXA Research Fund, and the Barcelona Supercomputing Center (grant nos. RES-AECT-2021-1-0027 and RES-AECT-2021-2-0001)., Peer Reviewed, Postprint (author's final draft)

We present an oceanographic research fiberglass reinforced polyester vessel of medium size (19.5 m length x 5.4 m beam) and plug-in hybrid propulsion complemented by a power generation system based on solar panels with polycrystalline cells connected to a charger and two wind turbines connected to their control systems. The vessel will be equipped for scientific research tasks in seas and coastal waters, with an operating cost that makes it viable in the long term, that is environmentally friendly, with an efficient management model, and that facilitates the collection of oceanographic data of high technical quality. [...]