This paper exploits a real-world scenario of significant emission reductions, such as that provided by the COVID-19 pandemic, to assess the responsiveness of an air quality model to real-world emission changes across Europe. The assessment is performed by evaluating the CHIMERE chemical transport model results against observation-based estimates derived from five-year mean concentrations, a Generalised Additive Model, and, for Spain, Gradient Boosting Machine. The impacts estimated by CHIMERE agree quite well with the observation-based estimates, with larger differences in some parts of northern Italy and northern Spain. All methodologies demonstrate generalized and robustly agreed reductions in NO2 concentrations. Regarding O3, the results from the observation-based methodologies concur with the differing impacts estimated by CHIMERE depending on the metric used. Consistent across all methods, the largest O3 reductions were found for metrics influenced by periods with higher solar radiation. Conversely, for the annual mean in areas with high NOx emissions, all methodologies consistently estimate O3 increases, a non-linear response driven by reduced NO-titration that validates the model's ability to capture complex chemical dynamics. By successfully validating CTM responsiveness under real-world emission shifts, this study indicates that these models can be considered useful tools for evaluating future emission reduction scenarios in air quality planning, although considering the uncertainties in areas where local conditions are challenging to model.

Recently, air quality has become a major concern for policy makers around the world, which has led to the implementation of mitigation measures. In urban areas, most measures affect the road transport sector, as this is one of the main contributors to air pollution in those areas. Due to the fact that spatial variability of urban air pollution is very heterogeneous, high spatial resolution modelling is necessary. In this context, this study aims to evaluate the air quality impacts of several measures applied to the traffic network around a real urban hot-spot (Plaza Elíptica, Madrid) at high spatial resolution. The methodology used is based on Computational Fluids Dynamics (CFD) modelling, but uses different modelling tools to obtain all the necessary input data. The SUMO microscopic traffic simulator is used to obtain a dataset of traffic flows for each scenario selected in the study. This dataset represents the regular traffic during the week, avoiding the cost of computational time and resources to run simulations for each hour. Emissions are computed for each timestep of the simulations (0.75 s) using the emissions model PHEMLight5 coupled with SUMO. A set of steady-state CFD simulations are previously performed for all wind direction sectors and scenarios, using the previously described emissions. The horizontal spatial resolution of these simulations is of 5x5 m2, which higher resolutions (up to 1x1 m2) near buildings. Relevant meteorological variables are obtained from WRF simulations using the urban parameterization BEP-BEM. These are necessary for both selecting the appropriate CFD simulations from the dataset according to the observed wind direction at each hour and estimating NOx maps from pre-calculated CFD simulations based on the wind speed observed at each hour. Finally, background NOx concentrations are obtained from an urban background air quality monitoring station (AQMS) in Madrid, located 1.6 km NW from the AQMS of Plaza Elíptica. Using this methodology, we have studied four scenarios: Base scenario. (Year 2016) Reorganization of traffic flows by changing traffic directions in some streets. (Year 2019) The initial phase of the implementation of a Low Emissions Zone (ZBE) affecting the most polluting vehicles; with still some reduction of traffic due to the COVID-19 pandemic. (Year 2022) The recovery of traffic after the COVID-19 pandemic. (Year 2023) Results were evaluated for February 2016, 2019, 2022 and 2023 using the observed concentrations at the AQMS in the study area. The impacts of the traffic variations are investigated for different meteorological conditions.

One relevant effect of urbanization is the modification of atmosphere-surface interactions, which modulate urban microclimate and human thermal comfort. The Universal Thermal Climate Index (UTCI) is commonly employed to quantify the impact of heat on the human body, accounting for not only air temperature influence but also the variability of other relevant weather variables such as wind speed, air humidity and radiation. The irregularity of urban morphology (e.g. building height and layout) across the city leads to high spatial heterogeneity of the micrometeorological variables. Therefore, analyzing the impact of urban geometry and the past changes in urban land cover on heat stress contributes to understanding the potential risks that urban residents might face considering the future urban growth and future climate.The purpose of the present work is to investigate the impact of urban development and climate on outdoor thermal comfort in Madrid for summer weather conditions under past and future climate. A modeling study is conducted using the Weather, Research and Forecasting (WRF) model adapted to estimate the heat and momentum exchanges between buildings and atmosphere (BEP-BEM urban scheme), as well as the recent development incorporated into BEP-BEM to quantify heat stress through UTCI values and its subgrid variability. Past urban scenarios are performed considering the realistic urban expansion and morphology from 1970 to 2020, and the expected urban development is used for the future scenario. Even though the urban layout has barely changed in the center of Madrid over the last 50 years, results show an increase in the UTCI values due to the influence of the surrounding urban expansion. In addition, these results show the relative contribution of urbanization and climate effects on the heat stress changes across the city under the past and future climates.

This work presents the impacts on NOx emissions and concentrations of several mitigation strategies considering different meteorological conditions in a real air pollution hot spot. For this purpose, a methodology based on Computational Fluids Dynamics (CFD) has been used. The SUMO microscopic traffic simulator, coupled with an emissions model, is used to obtain road-traffic-related emissions for each selected scenario. These emissions are then used as input data to a set of steady-state CFD simulations which were previously performed for all wind direction sectors. Relevant meteorological variables are obtained from WRF simulations using the urban parameterization BEP-BEM. Finally, background NOx concentrations are obtained from an urban background air quality monitoring station (AQMS) in Madrid. Using this methodology, we have studied four periods: Year 2016: Base case.Year 2019: Reorganization of traffic flows by changing traffic directions in some streets.Year 2022: Implementation of a Low Emissions Zone (ZBE) affecting the most polluting vehicles; with still some reduction of traffic due to the COVID-19 pandemic.Year 2023: The recovery of traffic after the COVID-19 pandemic. Results were evaluated using the observed concentrations at the AQMS in the study area. The impacts of the traffic variations are investigated for different meteorological conditions. The results show that the meteorological conditions affect both local and background concentrations and its net changes can be comparable to those due to emission reductions. Furthermore, we have considered two additional scenarios for each period considering different future levels of insertion of electric vehicles included in the Spanish National Energy and Climate Plan to assess their potential impact on emissions and air quality. Preliminary results show that the emissions reduction resulting from the replacement of fossil-fuelled vehicles with electric vehicles in the study area is not linear and depends on the composition of the traffic float prior to the replacement.

The specific objectives of this work are to assess a Computational Fluid Dynamics (CFD) modelling performance through data of one experimental campaign, to quantify the impact of outdoor NOX traffic emissions on indoor NOX concentration and to investigate the natural ventilation using the infiltrated NOX concentration decay and the Air Changes per Hour (ACHs). For this purpose, NOX transport phenomena in a single-side naturally ventilated room in a real building in Madrid is investigated through an Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach and individual passive scalar transport equations for each source (parked vehicles with the engine idling, street traffic and urban background). The combination of this methodology with suitable boundary conditions properly reproduces the time evolution of Wind Speed (WS), Wind Direction (WD) and Turbulent Kinetic Energy (kappa), both inside the streets and above the buildings, even for WS < 1 m s(-1), and also outdoor and indoor NOX concentrations. In this case, urban background significantly contributes to the indoor concentration and idling vehicles just below the room can contribute between 10 % and 50 % to the total indoor concentration, even when their emissions are considerably smaller than those of traffic in nearby streets. The Indoor-Outdoor NOX concentration ratio (I/O) depends not only on the outdoor concentration (which, at the same time, depends on the atmospheric turbulence) but also on the ventilation (in this case, type Single-Sided Ventilation, SSV), showing a wide range of values. The impact of an indoor Heat Source (HS) below the open window on I/O is low, but under certain meteorological conditions, the stack pressure could be more important than the wind pressure. The time required to ventilate the room is 3.4 min. It has been obtained using the infiltrated NOX concentration decay and has been verified through the average ACH, < ACH(t)>. These results provide a better understanding of the impact of the meteorological conditions in outdoor-indoor NOX exchange by natural ventilation, which is the main goal of this research.

Recently, air quality has become a major concern for policy makers around the world, which has led to the implementation of mitigation measures. In particular, in urban areas most measures affect the road transport sector, as this is one of the main contributors to air pollution in those areas. Recent studies have pointed out the need to determine the importance of external factors such as the meteorological conditions on the net effect on air quality of mitigation strategies. Due to the strong spatial variability of urban air pollution, high spatial resolution modelling is necessary. In this work, the impacts on emissions and nitrogen oxides (NOx) concentrations of several mitigation strategies on a real air pollution hot spot in southern Madrid (Spain) are simulated at microscale under different meteorological conditions. The results show that the meteorological conditions affect local NOx concentrations, and its net changes can be comparable to those due to emission reductions. In particular, meteorological conditions in 2019 induced higher NOx concentrations than in 2016, despite the local emissions were reduced by 50 % from 2016 to 2019. On the other hand, the impact of the implementation of a Low Emissions Zone (LEZ) on NOx concentrations is small and consistent with values found in other LEZs around Europe. However, this impact varies up to 70 % depending on the meteorological conditions. The impacts of a mitigation strategy are largely influenced by the meteorological conditions, and therefore the achievement of the target reduction of concentrations pursued by these measures will depend on the meteorological conditions.

In the framework of the Forum for Air Quality Modelling in Europe (FAIRMODE), a modelling intercomparison exercise for computing NO2 long-term average concentrations in urban districts with a very high spatial resolution was carried out. This exercise was undertaken for a district of Antwerp (Belgium). Air quality data includes data recorded in air quality monitoring stations and 73 passive samplers deployed during one-month period in 2016. The modelling domain was 800 x 800 m2. Nine modelling teams participated in this exercise providing results from fifteen different modelling applications based on different kinds of model approaches (CFD - Computational Fluid Dynamics-, Lagrangian, Gaussian, and Artificial Intelligence). Some approaches consisted of models running the complete one-month period on an hourly basis, but most others used a scenario approach, which relies on simulations of scenarios representative of wind conditions combined with post-processing to retrieve a one-month average of NO2 concentrations. The objective of this study is to evaluate what type of modelling system is better suited to get a good estimate of long-term averages in complex urban districts. This is very important for air quality assessment under the European ambient air quality directives. The time evolution of NO2 hourly concentrations during a day of relative high pollution was rather well estimated by all models. Relative to high resolution spatial distribution of one-month NO2 averaged concentrations, Gaussian models were not able to give detailed information, unless they include building data and street-canyon parameterizations. The models that account for complex urban geometries (i.e. CFD, Lagrangian, and AI models) appear to provide better estimates of the spatial distribution of one-month NO2 averages concentrations in the urban canopy. Approaches based on steady CFD-RANS (Reynolds Averaged Navier Stokes) model simulations of meteorological scenarios seem to provide good results with similar quality to those obtained with an unsteady one-month period CFD-RANS simulations.

Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.

The OLMAT (Optimization of Liquid Metal Advanced Targets) facility has recently undergone the commissioning and start-up phases. Solid Titanium -Zirconium-Molybdenum (TZM) alloy and liquid tin (Sn) metallic targets were exposed to a hydrogen neutral beam injector (NBI) particle flux with power densities up to 58 +/- 14 MW/ m2, pulse duration up to 150 ms, and repetition rates up to 2 pulses/minute. These beam parameters are well above the estimates based on the typical performance of this NBI system when used for heating plasmas in the TJ-II stellarator. The parameters of the plasma generated through the interaction of the fast (32.5 keV) neutrals and ions and the solid were characterized by spectroscopic methods while surface temperature and total absorbed power were followed using pyrometry, infrared (IR) thermography, and calorimetry, respectively. Targets were visually monitored during the exposure and microscopically analyzed ex-situ. Electrical isolation of the target permitted recording the floating voltage during irradiation as well as for active biasing tests. In this work, a description of the facility, its operating parameters, and firsts results are provided and assessed as a new High Heat Flux (HHF) Facility for testing solid and liquid metal divertor targets under reactor-relevant heat load conditions.

BACKGROUND AND AIMS:We aimed to assess the associations of exposure to air pollutants and standard and advanced lipoprotein measures, in a nationwide sample representative of the adult population of Spain. METHODS:We included 4647 adults (>18 years), participants in the national, cross-sectional, population-based di@bet.es study, conducted in 2008-2010. Standard lipid measurements were analysed on an Architect C8000 Analyzer (Abbott Laboratories SA). Lipoprotein analysis was made by an advanced 1 H-NMR lipoprotein test (Liposcale®). Participants were assigned air pollution concentrations for particulate matter <10 μm (PM10 ), <2.5 μm (PM2.5 ) and nitrogen dioxide (NO2 ), corresponding to the health examination year, obtained by modelling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). RESULTS:In multivariate linear regression models, each IQR increase in PM10 , PM2.5 and NO2 was associated with 3.3%, 3.3% and 3% lower levels of HDL-c and 1.3%, 1.4% and 1.1% lower HDL particle (HDL-p) concentrations (p < .001 for all associations). In multivariate logistic regression, there was a significant association between PM10 , PM2.5 and NO2 concentrations and the odds of presenting low HDL-c (<40 mg/dL), low HDL-p (<p25) and higher LDL particle (LDL-p) concentrations (≥p75). In subgroup analyses there were stronger associations between PM10 and NO2 and low HDL-p in men (p for interaction .008 and .034), and between NO2 and low HDL-p in individuals with obesity (p for interaction .015). CONCLUSIONS:Our study shows an association between the exposure to air pollutants and blood lipids in the general population of Spain, suggesting a link to atherosclerosis.

This paper aims to assess the impact of individual measures for NOx emission reduction on NO 2 concentrations at very high spatial resolution in an urban district of Madrid City (Spain). A methodology based on a set of Computational Fluid Dynamics simulations for 16 meteorological scenarios combined with the CHIMERE model for background pollution is used to obtain annual NO 2 concentration maps. Two scenarios included in the Spanish National Air Pollution Control Programme are investigated: NOx emission reductions from the installation of more efficient boilers for domestic heating (ECOBOIL) and from the partly substitution of passenger cars with combustion engines by electric cars (EC). This analysis is extended to 9 additional scenarios of more ambitious implementation of electric vehicles in order to determine what the NOx emission reduction required for the annual mean NO 2 concentration EU limit value not being exceeded is. The ECOBOIL scenario has a very weak impact on the NO 2 concentrations. However, the EC scenario implies a more significant reduction of the NO 2 concentrations, but not enough to fully remove NO 2 limit value exceedances in the study area. A small additional (compared with the EC scenario) implementation of electric vehicles seems to fulfil that the spatially averaged NO 2 concentration be lower than the EU limit value, but the area with exceedances is still very large. However, stronger traffic emission reductions (80%) corresponding to the most ambitious scenarios are needed in order to reach that at least 95% of the domain is free of EU limit value exceedances.

Changes in primary emissions due to the COVID-19 lockdowns in Europe for the year 2020 have been estimated by considering fully open-access and near-real-time measured activity data from a wide range of information sources and with simple computational techniques. The estimates consist on a dataset of reduction factors that are both time- and country-dependent and provided for the following source categories: energy industry (power plants), manufacturing industry, road traffic, aviation, shipping and other stationary combustion activities such as residential and commercial-institutional activities. Inspired in other authors' estimates for COVID reductions, the advantage of this methodology is that there is no use of machine learning, making this procedure more accessible to the general scientific community. We have followed a fast methodology that takes advantage of observed relationships between variables (e.g. temperature and energy demand) without needing special algorithms for finding those relationships. The comparison of our estimates with others from other authors indicate a reasonable agreement and pointing out that emissions dropped by a 17% on average in Europe, with large differences between sectors of activities and spatial heterogeneity. The most affected sector was aviation, with a spatial-averaged variation of −63% in emissions since the implementation of first restrictions with respect business-as-usual values. 2020 emission changes with respect to business-as-usual values in countries ranges from a −13% in Norway and Poland to a more than −20% in several Mediterranean countries as well as the United Kingdom. Two main periods of emission reductions have been identified.

Background Recent reports have suggested that air pollution may impact thyroid function, although the evidence is still scarce and inconclusive. In this study we evaluated the association of exposure to air pollutants to thyroid function parameters in a nationwide sample representative of the adult population of Spain. Methods The Di@bet.es study is a national, cross-sectional, population-based survey which was conducted in 2008-2010 using a random cluster sampling of the Spanish population. The present analyses included 3859 individuals, without a previous thyroid disease diagnosis, and with negative thyroid peroxidase antibodies (TPO Abs) and thyroid-stimulating hormone (TSH) levels of 0.1-20 mIU/L. Participants were assigned air pollution concentrations for particulate matter <2.5μm (PM 2.5 ) and Nitrogen Dioxide (NO 2 ), corresponding to the health examination year, obtained by means of modeling combined with measurements taken at air quality stations (CHIMERE chemistry-transport model). TSH, free thyroxine (FT4), free triiodothyronine (FT3) and TPO Abs concentrations were analyzed using an electrochemiluminescence immunoassay (Modular Analytics E170 Roche). Results In multivariate linear regression models, there was a highly significant negative correlation between PM 2.5 concentrations and both FT4 (p<0.001), and FT3 levels ( p <0.001). In multivariate logistic regression, there was a significant association between PM 2.5 concentrations and the odds of presenting high TSH [OR 1.24 (1.01-1.52) p =0.043], lower FT4 [OR 1.25 (1.02-1.54) p =0.032] and low FT3 levels [1.48 (1.19-1.84) p =<0.001] per each IQR increase in PM 2.5 (4.86 μg/m 3 ). There was no association between NO 2 concentrations and thyroid hormone levels. No significant heterogeneity was seen in the results between groups of men, pre-menopausal and post-menopausal women. Conclusions Exposures to PM 2.5 in the general population were associated with mild alterations in thyroid function.

Urban air quality is a major problem for human health and green infrastructure (GI) is one of the potential mitigation measures used. However, the optimum GI design is still unclear. The purpose of this study is to provide some recommendation that could help in the design of the GI (mainly, the selection of locations and characteristics of trees and hedgerows). Aerodynamic and deposition effects of each vegetation element of different GI scenarios are investigated. Computational fluid dynamics (CFD) simulations of a wide set of GI scenarios in an idealized three-dimensional urban environment are performed. In conclusion, it was found that trees in the middle of the avenue (median strip) reduce street ventilation, and traffic-related pollutant concentrations increase, in particular for streets parallel to the wind. Trees in the sidewalks act as a barrier for pollutants emitted outside, specifically for a 45° wind direction. Regarding hedgerows, the most important effect on air quality is deposition and the effects of green walls and green roofs are limited to their proximity to the building surfaces.

Nowadays, it is necessary a better airborne transmission understanding of respiratory diseases in shared indoor and semi-indoor environments with natural ventilation in order to adopt effective people's health protection measures. The aim of this work is to evaluate the relative exposure to SARS-CoV 2 in a set of virtual scenarios representing enclosed and semi-enclosed terraces under different outdoor meteorological conditions. For this purpose, indoor CO2 concentration is used as a proxy for the risk assessment. Airflow and people exhaled CO2 in different scenarios are simulated through Computational Fluid Dynamics (CFD) modelling with Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach. Both spatial average concentrations and local concentrations are analyzed. In general, spatial average concentrations decrease as ventilation increases, however, depending on the people arrangement inside the terrace, spatial average concentrations and local concentrations can be very different. Therefore, for assessing the relative exposure to SARS-CoV 2 it is necessary to consider the indoor flow patterns between infectors and susceptibles. This research provides detailed information about CO2 dispersion in enclosed/semi-enclosed scenarios, which can be very useful for reducing the transmission risk through better natural ventilation designs and improving the classic risk models since it allows to check their hypotheses in real-world scenarios. Although CFD ventilation studies in indoor/semi-indoor environments have been already addressed in the literature, this research is focused on restaurant terraces, scenarios scarcely investigated. Likewise, one of the novelties of this study is to take into account the outdoor meteorological conditions to appropriately simulate natural ventilation.

Current European legislation aims to reduce the air pollutants emitted by European countries in the coming years. In this context, this article studies the effects on air quality of the measures considered for 2030 in the Spanish National Air Pollution Control Programme (NAPCP). Three different emission scenarios are investigated: a scenario with the emissions in 2016 and two other scenarios, one with existing measures in the current legislation (WEM2030) and another one considering the additional measures of NAPCP (WAM2030). Previous studies have addressed this issue at a national level, but this study assesses the impact at the street scale in three neighborhoods in Madrid, Spain. NO2 concentrations are modelled at high spatial resolution by means of a methodology based on computational fluid dynamic (CFD) simulations driven by mesoscale meteorological and air quality modelling. Spatial averages of annual mean NO2 concentrations are only estimated to be below 40 µg/m3 in all three neighborhoods for the WAM2030 emission scenarios. However, for two of the three neighborhoods, there are still zones (4–12% of the study areas) where the annual concentration is higher than 40 µg/m3. This highlights the importance of considering microscale simulations to assess the impacts of emission reduction measures on urban air quality.

This paper is devoted to the investigation of the relationship between concentrations of traffic-related pollutants at pedestrian level in the street and indoor pollutant concentrations inside different rooms of different floors of a standard building. CFD modelling covering the whole urban environment, including the interior of a target building, is used to explicitly simulate wind flow and pollutant dispersion outdoors and indoors. A wide range of scenarios considering different percentage and location of open windows and different wind directions is investigated. A large variability of indoor pollutant concentrations is found depending on the floor and configuration of the open/closed windows, as well as the wind direction and its incidence angle. In general, indoor pollutant concentrations decrease with floor, but this decrease is different depending on the scenario and the room investigated. For some conditions, indoor concentrations higher than the spatially averaged values in the street (up to a ratio of 1.4) are found in some rooms due to the high pollutant concentrations close to open windows. This behavior may lead, on average, to higher exposure inside the room than outside although, in general, indoor pollutant concentrations are lower than that found in the street at pedestrian level. Results are averaged for all scenarios and rooms being the average ratio between indoor and oudoor concentrations 0.56 ± 0.24, which is in accordance with previous studies in real buildings. This paper opens to a unified approach for the assessment of air quality of the total indoor and outdoor environment.

During the last few decades, European legislation has driven progress in reducing air pollution in Europe through emission mitigation measures. In this paper, we use a chemistry transport model to assess the impact on ambient air quality of the measures considered for 2030 in the for the scenarios with existing (WEM2030) and additional measures (WAM2030). The study estimates a general improvement of air quality for the WAM2030 scenario, with no non-compliant air quality zones for NO2, SO2, and PM indicators. Despite an improvement for O-3, the model still estimates non-compliant areas. For this pollutant, the WAM2030 scenario leads to different impacts depending on the indicator considered. Although the model estimates a reduction in maximum hourly O-3 concentrations, small increases in O-3 concentrations in winter and nighttime in the summer lead to increases in the annual mean in some areas and increases in other indicators (SOMO35 for health impacts and AOT40 for impacts on vegetation) in some urban areas. The results suggest that the lower NOx emissions in the WEM and WAM scenarios lead to less removal of O-3 by NO titration, especially background ozone in winter and both background and locally produced ozone in summer, in areas with high NOx emissions.

Persistent wintertime inversions over cities are the most critical conditions for air quality, and also one of the most challenging situations to simulate with a meteorological model. In the first part of this study, the ability of the meteorological model WRF, coupled with the multilayer urban canopy parameterization BEP-BEM, to simulate the evolution of the Planetary Boundary Layer Structure over the city of Madrid, Spain, during a multiday inversion episode, is assessed. The model results are evaluated against airport soundings, fourteen meteorological stations within and around the urban area, and remotely sensed surface temperatures. The study indicates that PBL structure is determined by the interaction between the urban and rural heat and momentum fluxes, the topography, and the downward turbulent transport of heat. The best air temperature spatial distribution is obtained when the 6th order horizontal filter is applied only to wind and not to temperature, and when the soil moisture is reduced to 25% of the initial value provided by the global scale model. However, the comparison against satellite surface temperature data indicates that with such a dry soil the model underestimates the surface temperatures during the night and overestimates them during the day in rural areas. This error compensation points to a likely deficiency in the PBL and surface schemes during the persistent inversions. In urban areas, the simulations with the urban canopy parameterization tend to overestimate the nocturnal surface and air temperatures, while they reproduce wind speed correctly. Finally, a new methodology to assess the model's capability to reproduce the spatial variability of air temperature is introduced, and the results show that the use of the multilayer urban canopy scheme and the adjustment of the soil moisture are both needed to improve the reproduction of such spatial distribution.

A correct simulation of the dispersion during wintertime thermal inversion is important not only to improve the physical understanding of the phenomena but also to design and evaluate strategies to improve air quality. In Part II of this study the simulations performed in Part I using WRF with the multilayer urban canopy scheme BEP-BEM, are used to simulate the dispersion during one of those episodes over Madrid, Spain, using a passive tracer representing NOx. The results are compared against NOx measurements obtained at 24 ground stations, grouped in 5 zones. Coherently with Part I, the analysis shows that the best results for dispersion are obtained when BEP-BEM is used and the soil moisture is reduced to 25% of the value provided by the global model. The results also show a strong spatial variability of dispersive conditions, with a tendency of the pollutants to accumulate in the topographical depressions. Furthermore, a simple methodology is proposed to derive NO2 from NOx concentrations based on an empirical fitting of two months of observations. The statistical indicators for NO2 computed in this way are similar to those obtained with photochemical models, making this approach a valid, and computationally efficient, alternative, in particular for forecasting purposes. In the last part of this contribution, the model is used to design and evaluate simple air pollution reduction strategies. In particular, it has been found that: 1) there is no pollutant accumulation from one day to the following one, so the air quality of one day is entirely determined by the emissions and meteorological conditions of that day, 2) displacing part of the emissions of the rush hours to the central hours of the day, when the dispersive conditions are more favorable, can significantly reduce the peaks, and to a lesser extent the daily mean, without changing the total amount of pollutants emitted.