Atmospheric Dispersion and Chemistry Models: Advances and Applications (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 22 January 2025 | Viewed by 5478

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Instituto Nacional de Tecnica Aeroespacial, 28850 Madrid, Spain
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Special Issue Information

Dear Colleagues,

This Special Issue is a follow-up of its first edition entitled "Atmospheric Dispersion and Chemistry Models: Advances and Applications" (https://www.mdpi.com/journal/atmosphere/special_issues/Atmospheric_Dispersion_Models), published in Atmosphere in 2023.

Atmospheric dispersion and chemical transport models (CTMs) are an essential tool in atmospheric chemistry and environmental sciences. From urban air pollution modeling to ozone depletion, these models give us a picture, at different scales, of the distribution of species concentrations and pollutant deposition rates, among other relevant quantities. These models help us to interpret observational data which, in some cases, are sparse and incomplete.

Many dispersion models and CTMs have been developed to date, employing both Eulerian and Lagrangian approaches, each mostly focused on a particular spatial scale and application. A large portion of them do not generate their own meteorological field, which is previously computed by an external meteorological model, i.e., a complete meteorological prediction is not required to be run for each dispersion simulation, significantly minimizing the computational times associated with an online approach.

Their usefulness is not limited to only scientific research, but also to supporting environmental decision making. Therefore, the characterization of model uncertainties and model validation play a central role in the development of model applications.

This Special Issue (SI) of the open access journal Atmosphere aims to cover papers related to all aspects involved in the development of atmospheric dispersion models and CTMs, such as the implementation of new physical and chemical schemes, online and offline coupling with meteorological models, application studies related to atmospheric transport and chemistry, urban air quality assessments, and model evaluation.

Dr. Daniel Viúdez-Moreiras
Guest Editor

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Keywords

  • atmospheric dispersion model
  • atmospheric chemistry model
  • model development
  • air quality modeling
  • air pollution modeling
  • atmospheric modeling and simulation
  • atmospheric measurement techniques
  • atmospheric chemistry

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Published Papers (4 papers)

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Research

25 pages, 648 KiB  
Article
Generalized 3D Model of Crosswind Concentrations and Deposition in the Atmospheric Boundary Layer
by Mehdi Farhane and Otmane Souhar
Atmosphere 2024, 15(9), 1054; https://doi.org/10.3390/atmos15091054 - 31 Aug 2024
Viewed by 460
Abstract
In this paper, we introduce a comprehensive solution aimed at enhancing our understanding of three-dimensional atmospheric pollutant dispersion. This innovative solution involves the development of a generalized model that extends previous research and is applicable to all parameterization schemes of these equations, including [...] Read more.
In this paper, we introduce a comprehensive solution aimed at enhancing our understanding of three-dimensional atmospheric pollutant dispersion. This innovative solution involves the development of a generalized model that extends previous research and is applicable to all parameterization schemes of these equations, including wind speed profiles and turbulent diffusion coefficients, while incorporating the dry deposition criterion. Our methodology involves subdividing the atmospheric boundary layer into distinct sub-layers, which facilitates a detailed examination of pollutant dispersion dynamics. Extensive validation with data from the Hanford experiment has demonstrated the accuracy of this solution in simulating pollutant concentrations. The results demonstrate that there is a strong correlation between the projected and observed concentrations, underscoring the statistical reliability of our approach. This validation situates the statistical indices of our solution within an acceptable range, confirming its accuracy in predicting atmospheric pollutant dispersion. These findings thus establish our solution as a valid and effective method for studying complex environmental phenomena. Full article
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15 pages, 2897 KiB  
Article
Application of Effective Conversion Rates between NO and NO2 in a Standard Airport Dispersion Model System
by Ulf Janicke
Atmosphere 2024, 15(5), 574; https://doi.org/10.3390/atmos15050574 - 8 May 2024
Viewed by 853
Abstract
The NO/NO2/O3 reaction mechanism of the standard VDI 3783 Part 19 was coupled to the Lagrangian particle model LASAT and quasi-stationary, individual plumes were calculated for a point source under various conditions. First-order conversion rates between NO and NO2 [...] Read more.
The NO/NO2/O3 reaction mechanism of the standard VDI 3783 Part 19 was coupled to the Lagrangian particle model LASAT and quasi-stationary, individual plumes were calculated for a point source under various conditions. First-order conversion rates between NO and NO2 were derived by fitting to these plumes and further simplified to sets of categorized conversion rates which depend on background NO2 concentration, atmospheric stability and time of the day. The rates were applied in the standard airport dispersion model system LASPORT and compared to measured NO2 concentrations at Los Angeles International Airport. The agreement between modelled and measured NO2 concentrations (weekly averages) and ratios NO2 over NOx at monitor stations dominated by airport emissions was in most cases better than a factor of 2 with a Pearson correlation coefficient of about 0.9 or above. Full article
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17 pages, 3273 KiB  
Article
Simulation of the Jet Fire Using Atmospheric Dispersion Modeling (ALOHA): A Case Study of Natural Gas Pipeline in Istanbul, Türkiye
by Remzi Besiktas, Hakki Baltaci and Bulent Oktay Akkoyunlu
Atmosphere 2024, 15(4), 456; https://doi.org/10.3390/atmos15040456 - 6 Apr 2024
Cited by 2 | Viewed by 1438
Abstract
Natural gas is known as a widely used energy source in residential, business and industrial areas. During the transportation of natural gas by pipelines, accidents occur due to various reasons, which can also lead to gas output. These accidents are events that have [...] Read more.
Natural gas is known as a widely used energy source in residential, business and industrial areas. During the transportation of natural gas by pipelines, accidents occur due to various reasons, which can also lead to gas output. These accidents are events that have the potential to pose important risks in terms of life and property safety, particularly in urban areas and surrounding of pipeline routings. In this study, accident scenarios were generated based on a natural gas distribution pipeline fire that occurred in Istanbul (NW Türkiye) on 28 April 2020 and the impact areas of the jet fire were calculated using the ALOHA program. The effects of source release factors (i.e., pipe length and diameter) and atmospheric conditions (i.e., wind speed, cloud cover, air temperature and relative humidity) on the thermal radiation threat distances associated with jet fire were calculated for the current and worst scenarios. As a result, it was found that pipe length and diameter have a significant effect on threat distances. In addition to the role of the synoptic circulation mechanism on the jet fire for the selected episodic event (position of low/high pressure centers), local atmospheric conditions also have an effect on the threat distance. From the modeling analysis, significant impact of wind speed, air temperature and relative humidity values on the threat distances were found. In the worst scenario, if there were strong northeasterly winds reaching 30.9 m per hour at the time of the jet fire, the threat distances would have been 21 m (red), 28 m (orange) and 42 m (yellow). This case shows that if a natural gas jet fire occurs under the influence of strong northeasterly winds (passing over the Black Sea without encountering any topographic obstacles), poisonous gas will be transported to long distances in a short time and will negatively affect social life and economy. Full article
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10 pages, 3125 KiB  
Article
Defining Detection Limits for Continuous Monitoring Systems for Methane Emissions at Oil and Gas Facilities
by Qining Chen, Yosuke Kimura and David T. Allen
Atmosphere 2024, 15(3), 383; https://doi.org/10.3390/atmos15030383 - 20 Mar 2024
Viewed by 1392
Abstract
Networks of fixed-point continuous monitoring systems are becoming widely used in the detection and quantification of methane emissions from oil and gas facilities in the United States. Regulatory agencies and operators are developing performance metrics for these systems, such as minimum detection limits. [...] Read more.
Networks of fixed-point continuous monitoring systems are becoming widely used in the detection and quantification of methane emissions from oil and gas facilities in the United States. Regulatory agencies and operators are developing performance metrics for these systems, such as minimum detection limits. Performance characteristics, such as minimum detection limits, would ideally be expressed in emission rate units; however, performance parameters such as detection limits for a continuous monitoring system (CMS) will depend on meteorological conditions, the characteristics of emissions at the site where the CMS is deployed, the positioning of CMS devices in relation to the emission sources, and the amount of time allowed for the CMS to detect an emission source. This means that certifying the performance of a CMS will require test protocols with well-defined emission rates and durations; initial protocols are now being used in field tests. Field testing results will vary, however, depending on meteorological conditions and the time allowed for detection. This work demonstrates methods for evaluating CMS performance characteristics using dispersion modeling and defines an approach for normalizing test results to standard meteorological conditions using dispersion modeling. Full article
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