2020
DOI: 10.1016/j.apr.2019.10.001
|View full text |Cite
|
Sign up to set email alerts
|

Performance evaluation of a multiscale modelling system applied to particulate matter dispersion in a real traffic hot spot in Madrid (Spain)

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
7
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
7

Relationship

1
6

Authors

Journals

citations
Cited by 27 publications
(7 citation statements)
references
References 63 publications
0
7
0
Order By: Relevance
“…STAR-CCM+, one of the most commonly used commercial CFD softwares, was selected for the street-level simulation. Previous studies had found an excellent correlation be-tween STAR-CCM+ simulated and measured values in simulating environmental and meteorological problems at street level (Borge et al, 2018;Santiago et al, 2020;Santiago et al, 2017). The model has functions such as geometric modelling, model pre-processing, the calculation execution, and post-processing of results.…”
Section: Star-ccm+ Configurationmentioning
confidence: 99%
“…STAR-CCM+, one of the most commonly used commercial CFD softwares, was selected for the street-level simulation. Previous studies had found an excellent correlation be-tween STAR-CCM+ simulated and measured values in simulating environmental and meteorological problems at street level (Borge et al, 2018;Santiago et al, 2020;Santiago et al, 2017). The model has functions such as geometric modelling, model pre-processing, the calculation execution, and post-processing of results.…”
Section: Star-ccm+ Configurationmentioning
confidence: 99%
“…Another issue is the uncertainty in the set-up information (e.g., the urban morphology and inlet conditions) and their influence on the CFD results (García- Sanchez et al 2014;Santiago et al 2020). 4) The governing equations of mesoscale and fluid dynamics models, including large-eddy simulations (LES), are similar but with very different types of assumption and thus different model coefficients.…”
Section: Counter Argumentsmentioning
confidence: 99%
“…The BUILD SIMUL (2021) 14: 407-419 https://doi.org/10.1007/s12273-020-0689-z energy exchange between urban surfaces and the atmosphere is considered by assuming simple street canyons; see, for example, the Building Energy Parameterization Scheme (BEP) proposed by Martilli et al (2002) and the BEP combined with the Building Energy Model (BEM) proposed by Salamanca et al (2010), which are both included in WRF. This configuration is usually employed to simulate urban environments (e.g., Salamanca et al 2011Salamanca et al , 2012Gutiérrez et al 2015) and has been coupled, in some cases, to CFD simulations (Sanchez et al 2017;Borge et al 2018;Santiago et al 2020). There is a fundamental difference between these two approaches:  Single layer UCPs need to represent the integral effect of all the buildings and translate it into a surface flux applied at the displacement height (the lowest level of the mesoscale model).…”
Section: Introductionmentioning
confidence: 99%
“…The spatial distribution of concentrations is very heterogeneous as a consequence of the complex air flows in the street due to the interaction between the atmosphere and urban obstacles. Strong gradients of pollutant concentrations have been found in field experiments [5][6][7] and in model studies [8][9][10][11][12][13][14][15][16][17]. This also means that the spatial representativeness of urban air quality monitoring stations (AQMS) is very limited [18][19][20].…”
Section: Introductionmentioning
confidence: 99%
“…High-resolution modelling is, therefore, necessary to capture the spatial variability of air pollutant concentrations and estimating population exposure appropriately. Computational fluid dynamic (CFD) models are adequate tools for this because they have a spatial resolution high enough to capture such variability and, in fact, have been successfully applied to simulate pollutant dispersion in real urban environments [11,14,16,[21][22][23][24][25]. The main limitation of these models is the high computational cost required that limits the size of the domain, and, in most of cases, makes it unfeasible to carry out unsteady simulations of long time periods (e.g., months, a year).…”
Section: Introductionmentioning
confidence: 99%