High Resolution Urban Air Quality Modeling by Coupling CFD and Mesoscale Models: a Review

Kadaverugu, Rakesh; Sharma, Asheesh; Matli, Chandrasekhar; Biniwale, Rajesh B.

doi:10.1007/s13143-019-00110-3

Cited by 52 publications

(22 citation statements)

References 163 publications

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“…The high spatiotemporal resolution of meteorological input data, such as 3-D air temperature, wind components, and turbulent kinetic energy fields, with an approximately 1 km resolution is the essential merit of the coupled WRF-CFD model [ 31 ]. The coupled WRF-CFD modeling approach provides accurate meteorological inputs from a mesoscale model in simulating realistic urban air quality at a high resolution [ 32 ].…”

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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“…The supplement of data from urban air quality models combined with citizen measurement data can add important information to the interpretation of citizen measurements, e.g., interesting questions arising from citizen measurements are the significance of different sources (source apportionment) and the influence of varying meteorological conditions, as well as the complex urban topography, which ultimately led to the observed air pollutant concentrations. These questions can be well addressed using Eulerian dispersion models, which solve the fluid-dynamic equations under the imposition of realistic meteorological boundary conditions [17,18]. Moreover, with multi-scale modeling approaches, it is also possible to discriminate local contributions from the long-range transport of atmospheric pollutants [19].…”

Section: Scientific Interpretation and Supportmentioning

confidence: 99%

“…During this period, citizen measurements are available within the city district Leipzig Gohlis along a track that traverses diverse neighborhoods, including garden plots, within surprisingly very high PM10 concentrations (>50 µg/m 3 ) that were measured (see Figure 7). meteorological boundary conditions [17,18]. Moreover, with multi-scale modeling approaches, it is also possible to discriminate local contributions from the long-range transport of atmospheric pollutants [19].…”

Section: Scientific Interpretation and Supportmentioning

confidence: 99%

Knowledge Transfer with Citizen Science: Luft-Leipzig Case Study

et al. 2021

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Community-based participatory research initiatives such as “hackAir”, “luftdaten.info”, “senseBox” “CAPTOR”, “CurieuzeNeuzen Vlaanderen”, “communityAQ”, and “Healthy Air, Healthier Children” campaign among many others for mitigating short-lived climate pollutants (SLCPs) and improving air quality have reported progressive knowledge transfer results. These research initiatives provide the research community with the practical four-element state-of-the-art method for citizen science. For the preparation-, measurements-, data analysis-, and scientific support-elements that collectively present the novel knowledge transfer method, the Luft-Leipzig project results are presented. This research contributes to science by formulating a novel method for SLCP mitigation projects that employ citizen scientists. The Luft-Leipzig project results are presented to validate the four-element state-of-the-art method. The method is recommended for knowledge transfer purposes beyond the scope of mitigating short-lived climate pollutants (SLCPs) and improving air quality.

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“…The state-of-the-art in urban air quality modeling now almost routinely incorporates the scales at which processes governing the atmospheric dispersion inside the urban planetary boundary layer (PBL) are explicitly represented (Benavides et al, 2019;Croitoru and Nastase, 2018;Kadaverugu et al, 2019). The reasons for this increase in physical detail are manifold.…”

Section: Introductionmentioning

confidence: 99%

An urban large-eddy-based dispersion model for marginal grid resolutions: CAIRDIO v1.0

Weger

Knoth

Heinold

2020

Preprint

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Abstract. The capability for high spatial resolutions is an important feature of accurate numerical models dedicated to simulate the large spatial variability of urban air pollution. On the one hand, the well established mesoscale chemistry transport models have their obvious short-comings attributed to their extensive use of paramterizations. On the other hand, obstacle resolving computational fluid dynamic models, while accurate, still often demand too high computational costs, to be applied on a regular and holistic basis. The major reason for the inflated numerical costs is the required horizontal resolution to meaningfully apply the obstacle discretization, which is most often based on boundary-fitted grids, like e.g. the marker-and-cell method. Here we present a large-eddy-simulation approach that uses diffusive obstacle boundaries, which are derived from a simplified diffusive interface approach for moving obstacles. The diffusive interface approach is well established in two-phase modeling, but to the author’s knowledge has not been applied in urban boundary layer simulations so far. Our dispersion model is capable of representing buildings over a wide range of spatial resolutions, including marginally coarse resolutions inaccessible for standard methods. This opens up a very promising opportunity for application of accurate air quality simulations and forecasts on entire mid-sized city domains. Furthermore, our approach is capable of incorporating the influence of the land orography by the additional optional use of terrain-following coordinates. We validated the dynamic core against a set of numerical benchmarks and a standard high-quality wind-tunnel data set for dispersion-model evaluation.

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High Resolution Urban Air Quality Modeling by Coupling CFD and Mesoscale Models: a Review

Cited by 52 publications

References 163 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

Knowledge Transfer with Citizen Science: Luft-Leipzig Case Study

An urban large-eddy-based dispersion model for marginal grid resolutions: CAIRDIO v1.0

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