A Gaussian puff model with optimal interpolation for air pollution modelling assessment

2008 ◽  
Vol 35 (1) ◽  
pp. 111 ◽  
Author(s):  
K.M. Mok ◽  
A.I. Miranda ◽  
K.U. Leong ◽  
C. Borrego
Keyword(s):  
Air Pollution ◽  
Optimal Interpolation ◽  
Air Pollution Modelling ◽  
Gaussian Puff ◽  
Gaussian Puff Model

scholarly journals Air pollution modelling using a Graphics Processing Unit with CUDA

2010 ◽  
Vol 181 (1) ◽  
pp. 105-112 ◽  
Author(s):  
F. Molnár ◽  
T. Szakály ◽  
R. Mészáros ◽  
I. Lagzi
Keyword(s):  
Air Pollution ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Air Pollution Modelling ◽  
Graphics Processing

Evaluation of the performance of different short-range atmospheric dispersion models for the monitoring of CH4 emissions from industrial facilities

2021 ◽  
Author(s):  
Bonaventure Fontanier ◽  
Pramod Kumar ◽  
Grégoire Broquet ◽  
Christopher Caldow ◽  
Olivier Laurent ◽  
...  
Keyword(s):  
High Frequency ◽  
Meteorological Data ◽  
Atmospheric Dispersion ◽  
Local Scale ◽  
Lagrangian Model ◽  
Dispersion Models ◽  
Industrial Facilities ◽  
Gaussian Plume ◽  
Gaussian Puff ◽  
Gaussian Puff Model

<p>Methane (CH<sub>4</sub>) is a powerful greenhouse gas which plays a major role in climate change. The accurate monitoring of emissions from industrial facilities is needed to ensure efficient emission mitigation strategies. Local-scale atmospheric inversions are increasingly being used to provide estimates of the rates and/or locations of CH<sub>4</sub> sources from industrial sites. They rely on local-scale atmospheric dispersion models, CH<sub>4</sub> measurements and inversion approaches. Gaussian plume models have often been used for local-scale atmospheric dispersion modelling and inversions of emissions, because of their simplicity and good performance when used in a flat terrain and relatively constant mean wind conditions. However, even in such conditions, failure to account for wind and mole fraction variability can limit the ability to exploit the full potential of these measurements at high frequency.</p><p>We study whether the accuracy of inversions can be increased by the use of more complex dispersion models. Our assessments are based on the analysis of 25 to 75-min CH<sub>4 </sub>controlled releases during a one-week campaign in October 2019 at the TOTAL’s TADI operative platform in Lacq, France (in a flat area). During this campaign, for each controlled release, we conducted near-surface in situ measurements of CH<sub>4</sub> mole fraction from both a mobile vehicle and a circle of fixed points around the emission area. Our inversions based on a Gaussian model and either the mobile or fixed-point measurements both provided estimates of the release rates with 20-30% precision.  </p><p>Here we focus on comparisons between modeling and inversion results when using this Gaussian plume model, a Lagrangian model “GRAL” and a Gaussian puff model. The parameters for the three models are based on high-frequency meteorological values from a single stationary 3D sonic anemometer. GRAL should have relatively good skills under low-wind speed conditions. The Gaussian puff is a light implementation of time-dependent modeling and can be driven by high-frequency meteorological data. The performance of these dispersion models is evaluated with various metrics from the observation field that are relevant for the inversion. These analyses lead to the exploration of new types of definitions of the observational constraint for the inversions with the Gaussian puff model, when using the timeseries from fixed measurement points. The definitions explore a range of metrics in the time domain as well as in the frequency domain.</p><p>Eventually, the Lagrangian model does not outperform the Gaussian plume model in these experiments, its application being notably limited by the short scales of the transport characteristics. On the other hand, the Gaussian puff model provides promising results for the inversion, in particular, in terms of comparison between the simulated and observed timeseries for fixed stations. Its performance when driven by a spatially uniform wind field is an incentive to explore the use of meteorological data from several sonic stations to parameterize its configuration. The fixed-point measurements are shown to allow for more robust inversions of the source location than the mobile measurements, with an average source localization error of the order of 10 m.</p>

scholarly journals Spatial air pollution modelling for a West-African town

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Sirak Zenebe Gebreab ◽  
Danielle Vienneau ◽  
Christian Feigenwinter ◽  
Hampâté Bâ ◽  
Guéladio Cissé ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Cost Effective ◽  
Epidemiological Studies ◽  
West African ◽  
Data Availability ◽  
Air Pollution Modelling ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Leave One Out

<p>Land use regression (LUR) modelling is a common approach used in European and Northern American epidemiological studies to assess urban and traffic related air pollution exposures. Studies applying LUR in Africa are lacking. A need exists to understand if this approach holds for an African setting, where urban features, pollutant exposures and data availability differ considerably from other continents. We developed a parsimonious regression model based on 48-hour nitrogen dioxide (NO<sub>2</sub>) concentrations measured at 40 sites in Kaédi, a medium sized West-African town, and variables generated in a geographic information system (GIS). Road variables and settlement land use characteristics were found to be important predictors of 48-hour NO<sub>2</sub> concentration in the model. About 68% of concentration variability in the town was explained by the model. The model was internally validated by leave-one-out cross-validation and it was found to perform moderately well. Furthermore, its parameters were robust to sampling variation. We applied the model at 100 m pixels to create a map describing the broad spatial pattern of NO<sub>2</sub> across Kaédi. In this research, we demonstrated the potential for LUR as a valid, cost-effective approach for air pollution modelling and mapping in an African town. If the methodology were to be adopted by environmental and public health authorities in these regions, it could provide a quick assessment of the local air pollution burden and potentially support air pollution policies and guidelines.</p>

An inventory of tree species in Europe—An essential data input for air pollution modelling

2008 ◽  
Vol 217 (3-4) ◽  
pp. 292-304 ◽  
Author(s):  
Carsten A. Skjøth ◽  
Camilla Geels ◽  
Martin Hvidberg ◽  
Ole Hertel ◽  
Jørgen Brandt ◽  
...  
Keyword(s):  
Air Pollution ◽  
Tree Species ◽  
Data Input ◽  
Air Pollution Modelling

Inverse air pollution modelling of urban-scale carbon monoxide emissions

1995 ◽  
Vol 29 (4) ◽  
pp. 497-516 ◽  
Author(s):  
Michael Mulholland ◽  
John H. Seinfeld
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Air Pollution Modelling

Air-Pollution modelling aspects: an overview.

2019 ◽  
pp. 79-95
Author(s):  
C Monojit ◽  
B Sangeeta ◽  
M Renu ◽  
A Amit
Keyword(s):  
Air Pollution ◽  
Air Pollution Modelling
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