scholarly journals Efficient and high-resolution simulation of pollutant dispersion in complex urban environments by island-based recurrence CFD

2021 ◽  
pp. 105172
Author(s):  
Yaxing Du ◽  
Bert Blocken ◽  
Sanaz Abbasi ◽  
Stefan Pirker
Keyword(s):  
High Resolution ◽  
Pollutant Dispersion ◽  
Urban Environments ◽  
Resolution Simulation

scholarly journals High resolution modelling of aerosol dispersion regimes during the CAPITOUL field experiment: from regional to local scale interactions

2011 ◽  
Vol 11 (15) ◽  
pp. 7547-7560 ◽  
Author(s):  
B. Aouizerats ◽  
P. Tulet ◽  
G. Pigeon ◽  
V. Masson ◽  
L. Gomes
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Field Experiment ◽  
Aerosol Particle ◽  
Pollutant Dispersion ◽  
Local Scale ◽  
Plume Dispersion ◽  
Urban Dynamics ◽  
The Impact ◽  
Resolution Simulation

Abstract. High resolution simulation of complex aerosol particle evolution and gaseous chemistry over an atmospheric urban area is of great interest for understanding air quality and processes. In this context, the CAPITOUL (Canopy and Aerosol Particle Interactions in the Toulouse Urban Layer) field experiment aims at a better understanding of the interactions between the urban dynamics and the aerosol plumes. During a two-day Intensive Observational Period, a numerical model experiment was set up to reproduce the spatial distribution of specific particle pollutants, from the regional scales and the interactions between different cities, to the local scales with specific turbulent structures. Observations show that local dynamics depends on the day-regime, and may lead to different mesoscale dynamical structures. This study focuses on reproducing these fine scale dynamical structures, and investigate the impact on the aerosol plume dispersion. The 500-m resolution simulation manages to reproduce convective rolls at local scale, which concentrate most of the aerosol particles and can locally affect the pollutant dispersion and air quality.

scholarly journals High resolution modelling of aerosol dispersion regimes during the CAPITOUL field experiment: from regional to local scale interactions

2010 ◽  
Vol 10 (12) ◽  
pp. 29569-29598 ◽  
Author(s):  
B. Aouizerats ◽  
P. Tulet ◽  
G. Pigeon ◽  
V. Masson ◽  
L. Gomes
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Field Experiment ◽  
Aerosol Particle ◽  
Pollutant Dispersion ◽  
Turbulent Structures ◽  
Urban Dynamics ◽  
Set Up ◽  
Aerosol Dispersion ◽  
Resolution Simulation

Abstract. High resolution simulation of complex aerosol particle evolution and gaseous chemistry over an atmospheric urban area is of great interest for understanding air quality and processes. In this context, the CAPITOUL (Canopy and Aerosol Particle Interactions in the Toulouse Urban Layer) field experiment aims at a better understanding of the interactions between the urban dynamics and the aerosol plumes. During a two-day Intensive Observational Period, a numerical model experiment was set up to reproduce the spatial distribution of specific particle pollutants, from the regional scales and the interactions between different cities, to the local scales with specific turbulent structures. Observations show that local dynamics is driven either by convective cells coexisting with rolls or only by rolls depending on the day-regime. The 500 meter resolution simulation manages to reproduce these rolls, which concentrate most of the aerosol particles and can locally affect the pollutant dispersion and air quality.

scholarly journals 2nd Edition of Instrumenting Smart City Applications with Big Sensing and Earth Observatory Data: Tools, Methods and Techniques

2021 ◽  
Vol 13 (7) ◽  
pp. 1310
Author(s):  
Gabriele Bitelli ◽  
Emanuele Mandanici
Keyword(s):  
High Resolution ◽  
Exponential Growth ◽  
Smart City ◽  
Earth Observation ◽  
Urban Environments ◽  
Observation Data ◽  
High Resolution Imagery ◽  
Observatory Data ◽  
Methods And Techniques ◽  
Earth Observation Data

The exponential growth in the volume of Earth observation data and the increasing quality and availability of high-resolution imagery are increasingly making more applications possible in urban environments [...]

Post-processing rainfall in a high-resolution simulation of the 1994 Piedmont flood

2021 ◽  
Author(s):  
Scott Meech ◽  
Stefano Alessandrini ◽  
William Chapman ◽  
Luca Delle Monache
Keyword(s):  
High Resolution ◽  
Post Processing ◽  
Resolution Simulation

scholarly journals On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1310
Author(s):  
Pablo Torres ◽  
Soledad Le Clainche ◽  
Ricardo Vinuesa
Keyword(s):  
Physical Phenomenon ◽  
Urban Pollution ◽  
Pollutant Dispersion ◽  
Urban Environments ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Thermal Fields ◽  
Use Of Data ◽  
Sustainability Challenges ◽  
New Research

Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated with them. Artificial intelligence and urban flows should be combined into a new research line, where classical data-driven tools and machine-learning algorithms can shed light on the physical mechanisms associated with urban pollution.

The Alboran Sea mesoscale in a long term high resolution simulation: Statistical analysis

2013 ◽  
Vol 72 ◽  
pp. 32-52 ◽  
Author(s):  
Alvaro Peliz ◽  
Dmitri Boutov ◽  
Ana Teles-Machado
Keyword(s):  
Statistical Analysis ◽  
High Resolution ◽  
Alboran Sea ◽  
Alborán Sea ◽  
Resolution Simulation

scholarly journals The Impact of Forcing Datasets on the High-Resolution Simulation of Tropical Storm Ivan (2004) in the Southern Appalachians

2012 ◽  
Vol 140 (10) ◽  
pp. 3300-3326 ◽  
Author(s):  
Xiaoming Sun ◽  
Ana P. Barros
Keyword(s):  
High Resolution ◽  
Global Analysis ◽  
Surface Wind ◽  
Tropical Storm ◽  
Southern Appalachians ◽  
Low Level ◽  
Simulated Precipitation ◽  
Forced Simulation ◽  
The Impact ◽  
Resolution Simulation

Abstract The influence of large-scale forcing on the high-resolution simulation of Tropical Storm Ivan (2004) in the southern Appalachians was investigated using the Weather Research and Forecasting model (WRF). Two forcing datasets were employed: the North American Regional Reanalysis (NARR; 32 km × 32 km) and the NCEP Final Operational Global Analysis (NCEP FNL; 1° × 1°). Simulated fields were evaluated against rain gauge, radar, and satellite data; sounding observations; and the best track from the National Hurricane Center (NHC). Overall, the NCEP FNL forced simulation (WRF_FNL) captures storm structure and evolution more accurately than the NARR forced simulation (WRF_NARR), benefiting from the hurricane initialization scheme in the NCEP FNL. Further, the performance of WRF_NARR is also negatively affected by a previously documented low-level warm bias in NARR. These factors lead to excessive precipitation in the Piedmont region, delayed rainfall in Alabama, as well as spatially displaced and unrealistically extreme rainbands during its passage over the southern Appalachians. Spatial filtering of the simulated precipitation fields confirms that the storm characteristics inherited from the forcing are critical to capture the storm’s impact at local places. Compared with the NHC observations, the storm is weaker in both NARR and NCEP FNL (up to Δp ~ 5 hPa), yet it is persistently deeper in all WRF simulations forced by either dataset. The surface wind fields are largely overestimated. This is attributed to the underestimation of surface roughness length over land, leading to underestimation of surface drag, reducing low-level convergence, and weakening the dissipation of the simulated cyclone.

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