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Atmospheric Dispersion of Pollutants in Urban Environments
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Atmospheric Dispersion of Pollutants in Urban Environments

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 32327

Special Issue Editor

Dr. Silvia Trini Castelli

E-Mail Website
Guest Editor
National Research Council, Institute of Atmospheric Sciences and Climate (CNR-ISAC) Torino Branch, 10133 Torino, Italy
Interests: Atmospheric dispersion modelling; Boundary-layer meteorology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since 2014, more than 50% of the world′s population is residing in urban areas. Urban areas represent hotspots for air pollution problems, given the presence of different pollution sources, such as traffic, industries, house heating. This is true especially for large and densely populated cities. This Special Issue is devoted to all theoretical, modelling, and observational aspects of atmospheric dispersion of pollutants in urban environments, characterized by distinctive processes due to the interaction of the atmospheric flow with the complex urban geometry. Studies on all scales are of interest, from the street scale to the city and regional scales, including those related to the effects of the urban heat island. The topics of interest of this Special Issue include the investigation and parameterization of all atmospheric processes related to dispersion, numerical modelling with different approaches at various scales, data analysis of observed quantities determining the dispersion of pollutants, in both real urban sites and physical models.

Dr. Silvia Trini Castelli
Guest Editor

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Keywords

  • urban air pollution
  • turbulence and dispersion
  • modelling
  • observations
  • open theoretical issues

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Published Papers (7 papers)

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Research

27 pages, 5987 KiB  
Article
Analysis of Air Pollution in Urban Areas with Airviro Dispersion Model—A Case Study in the City of Sheffield, United Kingdom
by Said Munir, Martin Mayfield, Daniel Coca, Lyudmila S Mihaylova and Ogo Osammor
Atmosphere 2020, 11(3), 285; https://doi.org/10.3390/atmos11030285 - 15 Mar 2020
Cited by 22 | Viewed by 9084
Abstract
Two air pollutants, oxides of nitrogen (NOx) and particulate matter (PM10), are monitored and modelled employing Airviro air quality dispersion modelling system in Sheffield, United Kingdom. The aim is to determine the most significant emission sources and their spatial variability. NOx [...] Read more.
Two air pollutants, oxides of nitrogen (NOx) and particulate matter (PM10), are monitored and modelled employing Airviro air quality dispersion modelling system in Sheffield, United Kingdom. The aim is to determine the most significant emission sources and their spatial variability. NOx emissions (ton/year) from road traffic, point and area sources for the year 2017 were 5370, 6774, and 2425, whereas those of PM10 (ton/year) were 345, 1449, and 281, respectively, which are part of the emission database. The results showed three hotspots of NOx, namely the Sheffield City Centre, Darnall and Tinsley Roundabout (M1 J34S). High PM10 concentrations were shown mainly between Sheffield Forgemasters International (a heavy engineering steel company) and Meadowhall Shopping Centre. Several emission scenarios were tested, which showed that NOx concentrations were mainly controlled by road traffic, whereas PM10 concentrations were controlled by point sources. Spatiotemporal variability and public exposure to air pollution were analysed. NOx concentration was greater than 52 µg/m3 in about 8 km2 area, where more than 66 thousand people lived. Models validated by observations can be used to fill in spatiotemporal gaps in measured data. The approach used presents spatiotemporal situation awareness maps that could be used for decision making and improving the urban infrastructure. Full article
(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants in Urban Environments)
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20 pages, 7946 KiB  
Article
Surface and Aerodynamic Parameters Estimation for Urban and Rural Areas
by Roberto Sozzi, Giampietro Casasanta, Virginia Ciardini, Sandro Finardi, Igor Petenko, Andrea Cecilia and Stefania Argentini
Atmosphere 2020, 11(2), 147; https://doi.org/10.3390/atmos11020147 - 29 Jan 2020
Cited by 7 | Viewed by 2642
Abstract
Numerical weather prediction models require an accurate parametrization of the energy budget at the air-ground interface, that can be obtained only through long-term atmospheric boundary layer measurements at different spatial and temporal scales. Despite their importance, such measurements are still scarce even in [...] Read more.
Numerical weather prediction models require an accurate parametrization of the energy budget at the air-ground interface, that can be obtained only through long-term atmospheric boundary layer measurements at different spatial and temporal scales. Despite their importance, such measurements are still scarce even in well-characterized areas. In this paper, a three-year dataset from four micrometeorological stations run by the Regional Agency for Environmental Protection of Lazio was analyzed to estimate albedo, zero-displacement height, roughness length and surface properties over Rome and its suburbs, characterizing differences and interconnections between urban, suburban and rural areas of the same municipality. The integral albedo coefficient at the zenith for the urban station was found to be almost twice that for suburban and rural stations. The zero-displacement height of the urban site was strongly dependent on wind direction, with values varying between 12.0 and 17.8 m, while the roughness length (≈1.5 m) was almost independent of upwind direction, but it was significantly higher than the typical values calculated for rural stations (≈0.4 m). The apparent thermal capacities and thermal conductivity at all the non-urban sites were in fair agreement with each other and typical of soils with relatively low water content, as expected for a relatively dry Mediterranean area like Rome, while the apparent thermal diffusivity reflected the presence of different soil types. Full article
(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants in Urban Environments)
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14 pages, 12158 KiB  
Article
Monitoring and Modeling Roof-Level Wind Speed in a Changing City
by Kathrin Baumann-Stanzer, Sirma Stenzel, Gabriele Rau, Martin Piringer, Felix Feichtinger and Théophane Costabloz
Atmosphere 2020, 11(1), 87; https://doi.org/10.3390/atmos11010087 - 10 Jan 2020
Cited by 2 | Viewed by 2849
Abstract
Results of an observational campaign and model study are presented demonstrating how the wind field at roof-level in the urban area of Vienna changed due to the construction of a new building nearby. The investigation was designed with a focus on the wind [...] Read more.
Results of an observational campaign and model study are presented demonstrating how the wind field at roof-level in the urban area of Vienna changed due to the construction of a new building nearby. The investigation was designed with a focus on the wind energy yield of a roof-mounted small wind turbine but the findings are also relevant for air dispersion applications. Wind speed profiles above roof top are simulated with the complex fluid dynamics (CFD) model MISKAM (Mikroskaliges Klima- und Ausbreitungsmodell, microscale climate and dispersion model). The comparison to mast measurements reveals that the model underestimates the wind speeds within the first few meters above the roof, but successfully reproduces wind conditions at 10 m above the roof top (corresponding to about 0.5 times the building height). Scenario simulations with different building configurations at the adjacent property result in an increase or decrease of wind speed above roof top depending on the flow direction at the upper boundary of the urban canopy layer (UCL). The maximum increase or decrease in wind speed caused by the alternations in building structure nearby is found to be in the order of 10%. For the energy yield of a roof-mounted small wind turbine at this site, wind speed changes of this magnitude are negligible due to the generally low prevailing wind speeds of about 3.5 m s−1. Nevertheless, wind speed changes of this order could be significant for wind energy yield in urban areas with higher mean wind speeds. This effect in any case needs to be considered in siting and conducting an urban meteorological monitoring network in order to ensure the homogeneity of observed time-series and may alter the emission and dispersion of pollutants or odor at roof level. Full article
(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants in Urban Environments)
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18 pages, 3922 KiB  
Article
Fine-Scale Modeling of Individual Exposures to Ambient PM2.5, EC, NOx, and CO for the Coronary Artery Disease and Environmental Exposure (CADEE) Study
by Michael Breen, Shih Ying Chang, Miyuki Breen, Yadong Xu, Vlad Isakov, Saravanan Arunachalam, Martha Sue Carraway and Robert Devlin
Atmosphere 2020, 11(1), 65; https://doi.org/10.3390/atmos11010065 - 3 Jan 2020
Cited by 9 | Viewed by 3278
Abstract
Air pollution epidemiological studies often use outdoor concentrations from central-site monitors as exposure surrogates, which can induce measurement error. The goal of this study was to improve exposure assessments of ambient fine particulate matter (PM2.5), elemental carbon (EC), nitrogen oxides (NO [...] Read more.
Air pollution epidemiological studies often use outdoor concentrations from central-site monitors as exposure surrogates, which can induce measurement error. The goal of this study was to improve exposure assessments of ambient fine particulate matter (PM2.5), elemental carbon (EC), nitrogen oxides (NOx), and carbon monoxide (CO) for a repeated measurements study with 15 individuals with coronary artery disease in central North Carolina called the Coronary Artery Disease and Environmental Exposure (CADEE) study. We developed a fine-scale exposure modeling approach to determine five tiers of individual-level exposure metrics for PM2.5, EC, NOx, and CO using outdoor concentrations, on-road vehicle emissions, weather, home building characteristics, time-locations, and time-activities. We linked an urban-scale air quality model, residential air exchange rate model, building infiltration model, global positioning system (GPS)-based microenvironment model, and accelerometer-based inhaled ventilation model to determine residential outdoor concentrations (Cout_home, Tier 1), residential indoor concentrations (Cin_home, Tier 2), personal outdoor concentrations (Cout_personal, Tier 3), exposures (E, Tier 4), and inhaled doses (D, Tier 5). We applied the fine-scale exposure model to determine daily 24 h average PM2.5, EC, NOx, and CO exposure metrics (Tiers 1–5) for 720 participant-days across the 25 months of the CADEE study. Daily modeled metrics showed considerable temporal and home-to-home variability of Cout_home and Cin_home (Tiers 1–2) and person-to-person variability of Cout_personal, E, and D (Tiers 3–5). Our study demonstrates the ability to apply an urban-scale air quality model with an individual-level exposure model to determine multiple tiers of exposure metrics for an epidemiological study, in support of improving health risk assessments. Full article
(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants in Urban Environments)
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30 pages, 13241 KiB  
Article
Numerical Simulation of Turbulent Flow and Pollutant Dispersion in Urban Street Canyons
by Van Thinh Nguyen, Thanh Chuyen Nguyen and John Nguyen
Atmosphere 2019, 10(11), 683; https://doi.org/10.3390/atmos10110683 - 7 Nov 2019
Cited by 23 | Viewed by 5138
Abstract
In this study, we have developed a numerical model based on an open source Computational Fluid Dynamics (CFD) package OpenFOAM, in order to investigate the flow pattern and pollutant dispersion in urban street canyons with different geometry configurations. In the new model, the [...] Read more.
In this study, we have developed a numerical model based on an open source Computational Fluid Dynamics (CFD) package OpenFOAM, in order to investigate the flow pattern and pollutant dispersion in urban street canyons with different geometry configurations. In the new model, the pollutant transport driven by airflow is modeled by the scalar transport equation coupling with the momentum equations for airflow, which are deduced from the Reynolds Averaged Navier-Stokes (RANS) equations. The turbulent flow calculation has been calibrated by various two-equation turbulence closure models to select a practical and efficient turbulence model to reasonably capture the flow pattern. Particularly, an appropriate value of the turbulent Schmidt number has been selected for the pollutant dispersion in urban street canyons, based upon previous studies and careful calibrations against experimental measurements. Eventually, the numerical model has been validated against different well-known laboratory experiments in regard to various aspect ratios (a relationship between the building height and the width of the street canyon), and different building roof shapes (flat, shed, gable and round). The comparisons between the numerical simulations and experimental measurements show a good agreement on the flow pattern and pollutant distribution. This indicates the ability of the new numerical model, which can be applied to investigate the wind flow and pollutant dispersion in urban street canyons. Full article
(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants in Urban Environments)
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16 pages, 6638 KiB  
Article
Combining Dispersion Modeling and Monitoring Data for Community-Scale Air Quality Characterization
by Vlad Isakov, Saravanan Arunachalam, Richard Baldauf, Michael Breen, Parikshit Deshmukh, Andy Hawkins, Sue Kimbrough, Stephen Krabbe, Brian Naess, Marc Serre and Alejandro Valencia
Atmosphere 2019, 10(10), 610; https://doi.org/10.3390/atmos10100610 - 10 Oct 2019
Cited by 8 | Viewed by 4936
Abstract
Spatially and temporally resolved air quality characterization is critical for community-scale exposure studies and for developing future air quality mitigation strategies. Monitoring-based assessments can characterize local air quality when enough monitors are deployed. However, modeling plays a vital role in furthering the understanding [...] Read more.
Spatially and temporally resolved air quality characterization is critical for community-scale exposure studies and for developing future air quality mitigation strategies. Monitoring-based assessments can characterize local air quality when enough monitors are deployed. However, modeling plays a vital role in furthering the understanding of the relative contributions of emissions sources impacting the community. In this study, we combine dispersion modeling and measurements from the Kansas City TRansportation local-scale Air Quality Study (KC-TRAQS) and use data fusion methods to characterize air quality. The KC-TRAQS study produced a rich dataset using both traditional and emerging measurement technologies. We used dispersion modeling to support field study design and analysis. In the study design phase, the presumptive placement of fixed monitoring sites and mobile monitoring routes have been corroborated using a research screening tool C-PORT to assess the spatial and temporal coverage relative to the entire study area extent. In the analysis phase, dispersion modeling was used in combination with observations to help interpret the KC-TRAQS data. We extended this work to use data fusion methods to combine observations from stationary, mobile measurements, and dispersion model estimates. Full article
(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants in Urban Environments)
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17 pages, 8901 KiB  
Article
Parallelization Performances of PMSS Flow and Dispersion Modeling System over a Huge Urban Area
by Oliver Oldrini, Patrick Armand, Christophe Duchenne and Sylvie Perdriel
Atmosphere 2019, 10(7), 404; https://doi.org/10.3390/atmos10070404 - 16 Jul 2019
Cited by 20 | Viewed by 3379
Abstract
The use of modeling as a support tool for crisis management and decision planning requires fast simulations in complex built-up areas. The Parallel Micro SWIFT SPRAY (PMSS) modeling system offers a tradeoff between accuracy and fast calculations, while retaining the capability to model [...] Read more.
The use of modeling as a support tool for crisis management and decision planning requires fast simulations in complex built-up areas. The Parallel Micro SWIFT SPRAY (PMSS) modeling system offers a tradeoff between accuracy and fast calculations, while retaining the capability to model buildings at high resolution in three dimensions. PMSS has been applied to actual areas of responsibilities of emergency teams during the EMERGENCIES (very high rEsolution eMERGEncy simulatioN for citIES) and EMED (Emergencies for the MEDiterranean sea) projects: these areas cover several thousands of square kilometers. Usage of metric meshes on such large areas requires domain decomposition parallel algorithms within PMSS. Sensitivity and performance of the domain decomposition has been evaluated both for the flow and dispersion models, using from 341 up to 8052 computing cores. Efficiency of the Parallel SWIFT (PSWIFT) flow model on the EMED domain remains above 50% for up to 4700 cores. Influence of domain decomposition on the Parallel SPRAY (PSPRAY) Lagrangian dispersion model is less straightforward to evaluate due to the complex load balancing process. Due to load balancing, better performance is achieved with the finest domain decomposition. PMSS is able to simulate accidental or malevolent airborne release at high resolution on very large areas, consistent with emergency team responsibility constrains, and with computation time compatible with operational use. This demonstrates that PMSS is an important asset for emergency response applications. Full article
(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants in Urban Environments)
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