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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)

En la actualidad un factor fundamental de éxito de los proyectos es la satisfacción de las necesidades y expectativas de los interesados, ya que son ellos los que proporcionan los recursos, presentan las necesidades para la realización de los proyectos, y aceptan o no el resultado de los mismos. Con la realización de estos proyectos se permite la sostenibilidad de las empresas y el desarrollo de las comunidades. Esta investigación tiene el propósito de diseñar una guía de buenas prácticas para la gestión de interesados de los proyectos de mejora realizados por Megainversiones S.A. Su diseño fue basado en los diferentes estándares de gestión de proyectos, principalmente PMI (2017), y en las teorías, metodologías y modelos de procedencia, internos o externos, (Orpwood, 1985; Kloppenborg, 2009 y Trentim, 2015) matriz de poder – influencia / interés (Gardner, 1986), nivel de participación (PMI, 2017) y prominencia (Mitchell, Agle y Wood, 1997), de tal forma que puedan concluir con éxito sus proyectos. Es una inve

Barcelona city (Spain) is applying a series of traffic restriction measures that aim at renewing and reducing the amount of circulating vehicles to improve air quality. The measures include changes in the built environment to reduce private vehicle space in specific areas through the so-called “superblocks” and tactical urban planning actions, along with the implementation of a city-wide Low Emission Zone (LEZ) that restricts the entry of the most polluting vehicles to the city. Our study quantifies the impact of these measures in the greater area of Barcelona combining a coupled macroscopic traffic and pollutant emission model with a multi-scale air quality model. Our modelling system allows estimating the effect of different traffic restrictions upon traffic and the associated emissions and air quality levels at a very high resolution (20 m). The measures were evaluated both individually and collectively to assess both their relative and overall impact upon emissions and air quality. We show that in the absence of traffic demand reductions, the application of isolated measures that reduce private vehicle space, either through superblocks or tactical urban planning, have no overall emission impacts; only localized street-level NOx positive and negative changes (±17%) are found due to traffic re-routing and the generation of new bottlenecks. It is only when these measures are combined with optimistic fleet renewal as a result of the LEZ implementation and demand reductions, that relevant global emission reductions in NOx are obtained (-13% and -30%, respectively) with estimated NO2 reductions of -36% and -23% at the two traffic air quality monitoring stations. Despite the potential improvements, our simulations suggest that current measures are insufficient to comply with EU air quality standards and that further traffic restriction policies to reduce traffic demand are needed., The authors acknowledge CARNET-The Future Mobility Research HUB to allow the usage and work on the BCN-VML network, as well as PTV VISUM for the traffic software license. The author thankfully acknowledges the computer resources at MareNostrum and the technical support pro- vided by Barcelona Supercomputing Center (PRACE, AECT-2020-1-0007, AECT-2021-1-0027). The authors also acknowledge the support from the Ministerio de Ciencia, Innovación y Universidades (MICINN) as part of the BROWNING project RTI2018-099894-B-I00 and NUTRIENT project CGL2017-88911-R and the support from the Agencia Estatal de Investigacion (AEI) as part of the VITALISE project (PID2019-108086RA- I00/AEI/10.13039/501100011033). Carlos Pérez García-Pando acknowl- edges the long-term support from the AXA Chair in Sand and Dust Storms (AXA Research Fund), as well as the support received through the Ramón y Cajal programme (grant RYC-2015-18690) of the Spanish Ministry of Economy and Competitiveness., Peer Reviewed, Postprint (published version)

NOX emissions from diesel light-duty-vehicles (LDV) largely exceed the Euro emission standards in real-world driving conditions. Recent studies have quantified their impact upon air quality and human health primarily based on air quality models at mesoscale and large-scale resolutions. Here, we show that these approaches can significantly underestimate the impact of diesel LDV excess NOX emissions upon NO2 pollution in cities, particularly in the more compact and heavily trafficked ones. We compare an air quality mesoscale model at both 4 and 1 km resolution with a street-scale model in Barcelona, a compact city where the EU annual NO2 limits are repeatedly exceeded and a large share of passenger cars are diesel (65%). We compare consistently two emissions scenarios: a business-as-usual scenario where diesel LDV emit NOX in excess, and a counterfactual standard limits scenario where emissions are compliant with the Euro emission standards. We first show that in contrast to the mesoscale model, the street scale model is able to largely represent the observed NO2 concentration gradients between traffic and background stations in the city. In a second step, we find that the mesoscale model strongly underestimates the impact of diesel LDV excess NOX emissions upon NO2 pollution both in absolute terms (by 38%–48%) and relative terms (by 10%–35%). We argue that such underestimated impacts should be considered when assessing NOX excess emissions by LDV in cities. Using the street scale model, we find that diesel LDV excess NOX emissions are associated with about 20% of NO2 levels in the city, contributing substantially to an increased number of citizens exposed to high NO2 pollution in Barcelona., The authors thank the Generalitat de Catalunya for providing access to the measurements of the official monitoring network XVPCA and Pablo Martínez from the urban planning studio 300 000 km s−1 for providing the census-level population dataset disaggregated at the address level. The authors acknowledge PRACE and RES for awarding access to Marenostrum4 based in Spain at the Barcelona Supercomputing Center through the eFRAGMENT2 and AECT-2020-1-0007 projects. Jaime Benavides was funded by grant BES-2014-070637 from the FPI programme by the Spanish Ministry of the Economy and Competitiveness. The authors also acknowledge the support from the Ministerio de Ciencia, Innovación y Universidades (MICINN) as part of the BROWNING project RTI2018-099894-B-I00 and NUTRIENT project CGL2017-88911-R and the support from the Agencia Estatal de Investigacion (AEI) as part of the VITALISE project (PID2019-108086RA-I00/AEI/10.13039/501100011033). Carlos Pérez García-Pando acknowledges the long-term support from the AXA Research Fund, as well as the support received through the Ramón y Cajal programme (Grant RYC-2015-18690) of the Spanish Ministry of Economy and Competitiveness., Peer Reviewed, Postprint (published version)

Aplicat embargament des de la data de defensa fins a l'1 d0ctubre de 2021, Air pollution is known to cause detrimental health effects in cities and specially on the most vulnerable population. Having access to reliable air pollutant concentration data at street-level in urban areas can be crucial to mitigate the problem. In this thesis a street-scale air quality modelling system for the city of Barcelona (Spain) has been developed, evaluated and applied to an impact study. Aiming to produce more accurate air pollutant concentrations at street-level, we coupled a mesoscale air quality modelling system (CALIOPE) with an urban dispersion model (R-LINE). The developed modelling system, CALIOPE-Urban, incorporates novel methodologies to combine regional- to street-scale models. We faced two main methodological challenges in this thesis. First, the Gaussian dispersion model R-LINE was initially developed for open roads while Barcelona is a very built-up city, where diverse geometrical patterns cohabit. In order to apply R-LINE over Barcelona its meteorology has been adapted to street canyons. Second, the mesoscale meteorology and chemistry outputs of CALIOPE had to be adapted to drive pollutant dispersion and provide background concentrations to R-LINE, respectively. As a consequence, we developed a new methodology to calculate background concentrations at roof-top level and a vertical mixing parametrization to combine them with street-level freshly emitted pollutants. The vertical mixing parametrization considers urban geometry and atmospheric stability to calculate surface level background concentrations. In order to estimate turbulent parameters within a street canyon we built a new method to estimate local surface roughness specific for each street. In the first evaluation, we aimed to give a more accurate representation of NO2 spatio-temporal variability across Barcelona city with CALIOPE-Urban than with the mesoscale system alone. The temporal variability has been evaluated using measurements from five traffic sites and one urban backgroun, La contaminación del aire causa efectos perjudiciales para la salud en las ciudades y especialmente en los sectores de la población más vulnerables. Para mitigar este problema, es importante tener acceso a datos fiables de concentración de contaminantes en el aire a nivel de calle en zonas urbanas. En esta tesis hemos desarrollado, evaluado y aplicado un sistema de modelización de calidad del aire a escala de calle para la ciudad de Barcelona (España). Para ello, hemos acoplado un sistema de modelización regional de calidad del aire (CALIOPE) con un modelo de dispersión de contaminantes del tráfico rodado (R-LINE). Esta tesis nos ha presentado dos desafíos metodológicos principales. Primero, el modelo de dispersión gaussiano R-LINE se desarrolló inicialmente para zonas abiertas, mientras que Barcelona es una ciudad muy urbanizada, donde conviven calles con diversos patrones geométricos. Para aplicar R-LINE sobre Barcelona, su meteorología se ha adaptado a calles con edificios a ambos lados (tipo cañón urbano). En segundo lugar, hemos adaptado las salidas meteorológicas y químicas del sistema CALIOPE para facilitar la dispersión de contaminantes y proporcionar concentraciones de fondo a nivel de calle en R-LINE. Con ese objetivo, hemos desarrollado una nueva metodología para calcular las concentraciones de fondo por encima de los edificios y una parametrización de la mezcla atmosférica vertical para combinarlas con contaminantes recién emitidos a nivel de calle. En la primera evaluación, nuestro objetivo ha sido proporcionar una representación más precisa de la variabilidad espacio-temporal de NO2 en toda la ciudad de Barcelona con CALIOPE-Urban que con el sistema regional CALIOPE. La variabilidad temporal se ha evaluado utilizando mediciones realizadas en cinco zonas urbanas expuestas a tráfico y en una zona de fondo urbano en Abril-Mayo de 2013. Hemos hallado que CALIOPE-Urban ofrece una mayor precisión cerca del tráfico. Para la evaluación de la variabilidad espac, Postprint (published version)

Many urban areas suffer from poor air quality as a consequence of high levels of car-based traffic. Even cities with well-developed multi-modal public transport networks and favourable conditions for alternative transportation, such as Barcelona, experience problems with air pollution. The restrictions imposed on movement in response to the COVID-19 pandemic offer insights into the collective social benefits of reduced traffic. This situation also provided much-needed evidence about teleworking that will indicate whether it could become a mainstream and institutionalised practice in certain professions. In Barcelona, the experience of a less polluted, quieter and more liveable city has inspired both the municipal government and the citizens to rethink the use of public spaces and look for ways to reduce car dependency. We argue that this unprecedented crisis is an opportunity to create a more sustainable future of work and mobility in cities in the post-pandemic world., Peer Reviewed, Postprint (published version)