Prediction of high concentrations and concentration distribution of a continuous point source release in a semi-idealized urban canopy using CFD-RANS modeling

Efthimiou, George C.; Berbekar, Eva; Harms, Frank; Bartzis, John G.; Leitl, Bernd

doi:10.1016/j.atmosenv.2014.10.040

Cited by 24 publications

(12 citation statements)

References 34 publications

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“…The 3-D spatial distribution of near-road air pollution around hotspots is likely to be derived by the airflow around buildings, such as recirculating flows between roadside buildings and channeling flows inside building arrangements [ 25 , 26 , 27 ]. The peak concentration locations in a street canyon between buildings were substantially different within a 30 m altitude from the ground depending on the building geometries (i.e., height and symmetry) on both sides [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

Lee

Kwak

2020

IJERPH

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In this study, we have assessed the three-dimensional (3-D) spatial extent of near-road air pollution around a signalized intersection in a densely populated area using collaborating methodologies of stationary measurements, drone monitoring, and atmospheric dispersion modeling. Stationary measurement data collected in the roadside apartment building showed a substantial effect of emitted pollutants, such as nitrogen oxides (NOx), black carbon (BC), and ultrafine particles (UFPs), especially during the morning rush hours. Vertical drone monitoring near the road intersection exhibited a steeper decreasing trend with increasing altitude for BC concentration rather than for fine particulate matter (PM2.5) concentration below the apartment building height. Atmospheric NOx dispersion was simulated using the weather research and forecasting (WRF) and computational fluid dynamics (CFD) models for the drone measurement periods. Based on the agreement between the measured BC and simulated NOx concentrations, we concluded that the air pollution around the road intersection has adverse effects on the health of residents living within the 3-D spatial extent within at least 120 m horizontally and a half of building height vertically during the morning rush hours. The comparability between drone monitoring and WRF-CFD modeling can further guarantee the identification of air pollution hotspots using the methods.

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Section: Introductionmentioning

confidence: 99%

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

Lee

Kwak

2020

IJERPH

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“…In urban areas, this assessment can be performed using high-resolution models. In the last two decades, the characterization of the atmospheric turbulent flow and the pollutants dispersion in urban areas has been performed using physical models such as wind-tunnels [39], experimental campaigns [40] and numerical models [41]. The continuous improvement of computational resources capacities has supported the development of more and more complex numerical models followed by a noteworthy increase in the number of numerical studies of the turbulent flow dynamics and pollutants dispersion in highly complex urban areas.…”

Section: Assessment Of CC Impactsmentioning

confidence: 99%

Air quality, urban fluxes and cities resilience under climate change – A brief overview

Borrego¹,

Rafael²,

Rodrigues³

et al. 2018

Int. J. EI

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Cities are home of about 70% of the European population, and it is expected that by 2050 this number will be achieved around the world. As a result, cities are facing important challenges related to pressures induced by changes on urban metabolism and by climate change (CC) effects. Understanding the key factors determining the vulnerability of a city provides a framework to consider resilience. These issues become more and more relevant since changes in urban structure and metabolism together with CC will start affecting atmospheric emissions, urban air quality and consequently human health. Cobenefits of an urban air quality and CC approach need to be further addressed taking into consideration that CC creates both risks and opportunities. Therefore, an integrated assessment of the interaction between resilience factors and CC effects, and its influence on the urban microclimate and air quality, is required to better adapt to future climate. This knowledge is fundamental to support policy makers and stakeholders helping them to choose the best strategies to manage resources, to mitigate extreme weather events and to predict air pollution episodes. This article offers a systematic review on CC impacts in cities, providing some adaptation strategies and suggesting future research topics.

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“…Therefore additional criteria are needed to specify the appropriate confidence interval level [12]. In reality the maximum concentrations are real deterministic numbers and are expected to dilute downstream.…”

Section: Introductionmentioning

confidence: 99%

Modelling short term individual exposure from airborne hazardous releases in urban environments

Bartzis

Efthimiou

Andronopoulos

2015

Journal of Hazardous Materials

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Prediction of high concentrations and concentration distribution of a continuous point source release in a semi-idealized urban canopy using CFD-RANS modeling

Cited by 24 publications

References 34 publications

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

Air quality, urban fluxes and cities resilience under climate change – A brief overview

Modelling short term individual exposure from airborne hazardous releases in urban environments

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