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.

Urbanisation has intensified environmental challenges, particularly the deterioration of air quality and the amplification of heat stress, both of which directly affect public health and urban liveability [...]

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.

Heat stress depends on a set of metereological variables, namely, air temperature, wind speed, air humidity and mean radiant temperature. In urban areas, wind speed and mean radiant temperature are strongly spatially hetereogeneous, at scales of few meteres, much smaller than the typical resolution of mesoscale models, which is of the order of one kilometer or several hundreds of meters. This is the main obstacle to produce reliable estimates of heat stress at city scale. In this contribution, we present a methodology, built over a set of microscale simulations, to represent subgrid scale variability of wind speed and mean radiant temperature, and as a consequence heat stress. The scheme is implemented in the multilayer urban canopy parameterization BEP-BEM embedded in the mesoscale model WRF (therefore called WRF-comfort), and it opens the way to the city scale evaluation of the impact of different adaptation/mitigation strategies on heat stress, something that is essential to plan liveable future cities in the context of a changing climate. This is illustrated with a series of simulations for a summertime period over the city of Madrid (Spain). Then main outcome of the study is that the time evolution and spatial variability of UTCI (the Universal Thermal Climate Index, one of the most used heat stress indexes) are strongly affected by the urban morphology, and that the spatial pattern of UTCI at city scale is only partially similar to the one of air temperature, and dissimilar to the one of Land Surface Temperature, as it can be seen from satellite, a variable often used to assess urban overheating.

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.

Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

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 interactions between the atmosphere and urban obstacles such as buildings or vegetation induce complex flow patterns because of the heterogeneities of urban morphology [...]

In this study, to comprehensively investigate the impact of garden plants on air quality, we measured the leaves of 18 common garden plants in three different areas, namely, Suzhou industrial parks (clean air area (CAA)), Xiangcheng district parks (lightly polluted area (LPA)), and Huqiu district parks (highly polluted area (HPA)). We also measured the leaf functional traits of different life-types of plants. To explore the trade-off strategies of the leaf traits of common garden plants in response to air pollution and to assess the adaptive capacity of different life types of plants to air pollution. The results show that plants in the polluted area had higher leaf dry matter content (LDMC) and leaf nitrogen content per unit mass (Nmass), and a lower specific leaf area (SLA), maximum net photosynthetic rate per unit area (Aarea), transpiration rate (Tr), stomatal conductance (Gs), and chlorophyll value (SPAD). Pearson correlation analysis showed that SLA was significantly positively correlated with Nmass, Tr, photosynthetic use efficiency (PNUE), and SPAD, and significantly negatively correlated with LDMC, while Aarea was significantly positively correlated with chlorophyll value. Redundancy analysis revealed that the correlation between each leaf functional trait and atmospheric pollution factors was as follows: LDMC > Nmass > SLA > LA > Aarea > Tr > PNUE > SPAD. The results suggest that different plant types have varying levels of adaptability to environmental conditions. Trees were found to be the most adaptable, followed by shrubs, herbs, and lianas. Additionally, under the stress of air pollution, herbs and lianas exhibited characteristics of “fast investment-return” on the leaf economic spectrum, meaning they were able to quickly allocate resources to maximize their return. However, trees and shrubs displayed traits of “slow investment-return”, indicating a more conservative approach to resource allocation. These results provide valuable insights into the leaf trade-off strategies of plants in Suzhou Park under air pollution stress and can guide the selection of suitable plant species in similar environments.

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.

Air pollution in cities, especially in existing urban canyons, poses a global significant long-term health risk to the urban population, and urban planners are faced with the challenge of increasing the transport of pollutants out of cities. In recent years, many research and review articles have explored passive methods of altering the urban canyon geometry using 'obstacles' that alter the dispersion of air flow in these canyons, thereby enhancing pollutant dispersion. These obstacles have been categorised (in previous review articles) into porous and nonporous barriers. Porous barriers include vegetated shrubs and trees, while non-porous barriers include parked cars, low boundary walls, roadside barriers, wind catchers and solar chimneys. This paper expands on previous reviews to highlight newer studies, their findings, and challenges in implementing these measures for existing urban canyons. In addition, it attempts to bring us one step closer to developing urban design guidelines that improve air quality in the urban environment.

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.

Many research articles explore new designs and how to arrange barriers/obstacles to improve roadside air quality and ventilation within the urban street canyon. These obstacles are generally categorized into porous, non-porous and mixed type. Porous barriers include vegetated shrubs and trees; non-porous barriers include parked cars, low boundary walls, etc., while mixed barriers combine both porous and non-porous barriers. Moreover, new developments can benefit from added design flexibility using lift-up building design and building porosity as a promising way of improving ventilation. This short paper reviews the different research studies conducted on obstacles/barriers in an urban canyon which helps improve air quality and also highlights potential future research.

Health impacts of atmospheric pollution is an important issue in urban environments. Its magnitude depends on population exposure which have been frequently estimated by considering different approaches relating pollutant concentration and population exposed to it. However, the uncertainties due to the spatial resolution of the model used to estimate the pollutant concentration or due to the lack of representativeness of urban air quality monitoring station (AQMS) have not been evaluated in detail. In this context, NO2 annual average concentration at pedestrian level in the whole city of Pamplona (Spain) modelled at high spatial resolution (~1 m) by Computational Fluid Dynamic (CFD) simulations is used to estimate the total population exposure and health-related externalities by using different approaches. Air pollutant concentration and population are aggregated at different spatial resolutions ranging from a horizontal grid cell size of 100 m × 100 m to a coarser resolution where the whole city is covered by only one cell (6 km × 5 km). In addition, concentrations at AQMS locations are also extracted to assess the representativeness of those AQMS. The case with a spatial resolution of 100 m × 100 m for both pollutant-concentration distribution and population data is used as a reference (Base case) and compared with those obtained with the other approaches. This study indicates that the spatial resolution of concentration and population distribution in the city should be 1 km × 1 km or finer to obtain appropriate estimates of total population exposure (underestimations <13%) and health-related externalities (underestimations <37%). For the cases with coarser resolutions, a strong underestimation of total population exposure (>31%) and health-related externalities (>76%) was found. On the other hand, the use of AQMS concentrations can induce important errors due to the limited spatial representativeness, in particular in terms of population exposure.