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Atmospheric Dispersion and Chemistry Models: Advances and Applications

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

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 23654

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Special Issue Editor

Dr. Daniel Viúdez-Moreiras

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Instituto Nacional de Tecnica Aeroespacial, 28850 Madrid, Spain
Interests: modeling & simulation; planetary atmospheres; atmospheric dynamics and chemistry
Special Issues, Collections and Topics in MDPI journals

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Dear Colleagues,

Atmospheric dispersion and chemical transport models (CTMs) are a key 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 species concentrations’ distribution and pollutant deposition rates, among other relevant quantities. These models are able to make predictions in complex scenarios and help us to interpret the observational data, which are in some cases sparse and incomplete.

Many dispersion models and CTMs have been developed to date, both with 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. Their usefulness is not only constrained to scientific research, but also in support of environmental decision making. Thus, the characterization of model uncertainties and model validation plays a central role in the development applications for such models.

This Special Issue aims to publish 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, the 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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Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

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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

Published Papers (12 papers)

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Editorial

Jump to: Research

3 pages, 160 KiB

Open AccessEditorial

Editorial for the Special Issue “Atmospheric Dispersion and Chemistry Models: Advances and Applications”

by Daniel Viúdez-Moreiras

Atmosphere 2023, 14(8), 1275; https://doi.org/10.3390/atmos14081275 - 11 Aug 2023

Cited by 1 | Viewed by 655

Abstract

Atmospheric dispersion and chemical transport models (CTMs) are a key tool in both atmospheric chemistry and environmental sciences [...] Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

Research

Jump to: Editorial

19 pages, 38481 KiB

Open AccessArticle

Dispersion and Radiation Modelling in ESTE System Using Urban LPM

by Ľudovít Lipták, Peter Čarný, Michal Marčišovský, Mária Marčišovská, Miroslav Chylý and Eva Fojciková

Atmosphere 2023, 14(7), 1077; https://doi.org/10.3390/atmos14071077 - 26 Jun 2023

Cited by 1 | Viewed by 829

Abstract

In cases of accidental or deliberate incidents involving a harmful agent in urban areas, a detailed modelling approach is required to include the building shapes and spatial locations. Simultaneously, when applied to crisis management, a simulation tool must meet strict time constraints. This work presents a Lagrangian particle model (LPM) for computing atmospheric dispersion. The model is implemented in the nuclear decision support system ESTE CBRN, a software tool developed to calculate the atmospheric dispersion of airborne hazardous materials and radiological impacts in the built-up area. The implemented LPM is based on Thomson’s solution for the nonstationary, three-dimensional Langevin equation model for turbulent diffusion. The simulation results are successfully analyzed by testing compatibility with Briggs sigma functions in the case of continuous release. The implemented LPM is compared with the Joint Urban 2003 Street Canyon Experiment for instantaneous puff releases. We compare the maximum concentrations and peak times measured during two intensive operational periods. The modeled peak times are mostly 10–20% smaller than the measured. Except for a few detector locations, the maximum concentrations are reproduced consistently. In the end, we demonstrate via calculation on single computers utilizing general-purpose computing on graphics processing units (GPGPU) that the implementation is well suited for an actual emergency response since the computational times (including dispersion and dose calculation) for an acceptable level of result accuracy are similar to the modeled event duration itself. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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12 pages, 29817 KiB

Open AccessArticle

A Study on Radiological Hazard Assessment for Jordan Research and Training Reactor

by Mohammad Talafha, Sora Kim and Kyung-Suk Suh

Atmosphere 2023, 14(5), 859; https://doi.org/10.3390/atmos14050859 - 11 May 2023

Cited by 1 | Viewed by 1181

Abstract

Numerical simulations of atmospheric dispersion and dose assessment were performed for the Jordan Research and Training Reactor (JRTR) to evaluate its radiological effects on surrounding population and the environment. A three-dimensional atmospheric dispersion model was applied to investigate the behavior of the radionuclides released into the air, and a dose assessment model was used to estimate the radiological impact on the population residing in nearby cities around the JRTR. Considering full core meltdown an accidental scenario, most of the source term was assumed to be released from the JRTR. Simulations were performed to calculate the air and deposition concentrations of radioactive materials for July 2013 and January 2014. The monthly averaged values of concentrations, depositions, and dose rates were analyzed to identify the most harmful effects in each month. The results showed that relatively harmful effects occurred in January 2014, and the total annual dose rate was estimated to be approximately 1 mSv outside the 10 km radius from JRTR. However, the impact of a nuclear accident is not as severe as it might seem, as the affected area is not highly populated, and appropriate protective measures can significantly reduce the radiation exposure. This study provides useful information for emergency preparedness and response planning to mitigate the radiological consequences of a nuclear accident at the JRTR. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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30 pages, 2527 KiB

Open AccessArticle

A Coupled CH₄, CO and CO₂ Simulation for Improved Chemical Source Modeling

by Beata Bukosa, Jenny A. Fisher, Nicholas M. Deutscher and Dylan B. A. Jones

Atmosphere 2023, 14(5), 764; https://doi.org/10.3390/atmos14050764 - 22 Apr 2023

Cited by 1 | Viewed by 2481

Abstract

Understanding greenhouse gas–climate processes and feedbacks is a fundamental step in understanding climate variability and its links to greenhouse gas fluxes. Chemical transport models are the primary tool for linking greenhouse gas fluxes to their atmospheric abundances. Hence, accurate simulations of greenhouse gases [...] Read more.

_{2}

) and methane (CH

_{4}

)—along with the indirect greenhouse gas carbon monoxide (CO) based on their chemistry. Our updates include the online calculation of the chemical production of CO from CH

_{4}

and the online production of CO

_{2}

from CO, both of which were handled offline in the previous versions of these simulations. In the newly developed coupled (online) simulation, we used consistent hydroxyl radical (OH) fields for all aspects of the simulation, resolving biases introduced by inconsistent OH fields in the currently available uncoupled (offline) CH

_{4}

, CO and CO

_{2}

simulations. We compare our coupled simulation with the existing v12.1.1 GEOS-Chem uncoupled simulations run the way they are currently being used by the community. We discuss differences between the uncoupled and coupled calculation of the chemical terms and compare our results with surface measurements from the NOAA Global Greenhouse Gas Reference Network (NOAA GGGRN), total column measurements from the Total Carbon Column Observing Network (TCCON) and aircraft measurements from the Atmospheric Tomography Mission (ATom). Relative to the standard uncoupled simulations, our coupled results suggest a stronger CO chemical production from CH

_{4}

, weaker production of CO

_{2}

from CO and biases in the OH fields. However, we found a significantly stronger chemical production of CO

_{2}

in tropical land regions, especially in the Amazon. The model–measurement differences point to underestimated biomass burning emissions and secondary production for CO. The new self-consistent coupled simulation opens new possibilities when identifying biases in CH

_{4}

, CO and CO

_{2}

source and sink fields, as well as a better understanding of their interannual variability and co-variation. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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24 pages, 15609 KiB

Open AccessArticle

Assessment of Land Surface Schemes from the WRF-Chem for Atmospheric Modeling in the Andean Region of Ecuador

by Rene Parra

Atmosphere 2023, 14(3), 508; https://doi.org/10.3390/atmos14030508 - 6 Mar 2023

Cited by 2 | Viewed by 1613

Abstract

Surface interactions occur near the land–atmosphere interface, thus affecting the temperature, convection, boundary layer, and stability of the atmosphere. A proper representation of surface interactions is a crucial component for numerical atmospheric and air quality modeling. We assessed four land surface schemes—1. 5-layer thermal diffusion scheme (1 5-Layer); 2. unified Noah land surface model (2 Noah); 3. rapid update cycle (3 RUC) land surface model; and 4. Pleim–Xiu land surface model (4 Pleim–Xiu)—from the Weather Research and Forecasting with Chemistry (WRF-Chem V3.2) model for the purposes of atmospheric modeling in Cuenca, which is a region with a complex topography and land use configuration and which is located in the Southern Andean region, in Ecuador. For this purpose, we modeled the meteorological and air quality variables during September 2014. It was found that the meteorological and short-term air quality variables were better modeled through the 2 Noah scheme. Long-term (mean monthly) air quality variables were better modeled by the 1 5-Layer and 3 RUC options. On average, the 2 Noah scheme was better at modeling meteorology and air quality. In addition, we assessed the 2 Noah scheme combined with the urban canopy model (UCM) (5 Noah UCM), which was developed as an option to represent the urban effects at a subgrid-scale. Results indicated that the performance of the 5 Noah UCM scheme was not better at modeling than the 2 Noah scheme alone. Moreover, the 5 Noah UCM scheme notably decreased the modeling performance for carbon monoxide and fine particulate matter. These results complement previous assessments of other schemes, allowing us to recommend a basic configuration of parameters for atmospheric modeling in the Andean region of Ecuador. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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24 pages, 5897 KiB

Open AccessArticle

Ensemble of Below-Cloud Scavenging Models for Assessing the Uncertainty Characteristics in Wet Raindrop Deposition Modeling

by Alexey Kiselev, Alexander Osadchiy, Anton Shvedov and Vladimir Semenov

Atmosphere 2023, 14(2), 398; https://doi.org/10.3390/atmos14020398 - 18 Feb 2023

Cited by 3 | Viewed by 1440

Abstract

This work is devoted to the development of an ensemble of below-cloud scavenging models of pollutant aerosol transport into the atmosphere. Among other factors contributing to the uncertainty of the forecasts of the dispersion and deposition of technogenic gas-aerosol releases in the atmosphere, precipitation scavenging is one of the least studied and, in case of precipitation, can be the dominant mechanism for aerosol deposition. To form the ensemble of below-cloud scavenging models, appropriate experimental data, raindrop-aerosol capture models, raindrop terminal velocity parameterizations, and raindrop size distributions were chosen. The pool of models was prepared and then evaluated to adequately describe the experimental data using statistical analysis. Rank diagrams were used to analyze the adequacy of meteorological ensembles; together with the ensemble distribution construction, they allowed selecting the groups of models with such properties as to produce unbiased estimates and dispersion corresponding to the dispersion of the experimental data. The model calculations of the concentration fraction deposited due to below-cloud scavenging were performed using a log-normal distribution with characteristics corresponding to those observed during the accidents at the Chernobyl NPP and Fukushima-1 NPP. The results were compared with those obtained using the models of the NAME and FLEXPART codes. The results of this work can be used to improve the current approaches applied for modelling the distribution of pollutants in the atmosphere in the case of emergency, enhancing the reliability of forecasts by taking into account uncertainties in the results. The formed multi-model ensemble will be included in the decision support system used in responding to releases of radioactive substances into the atmosphere. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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17 pages, 1010 KiB

Open AccessArticle

Bayesian Inverse Modelling for Probabilistic Multi-Nuclide Source Term Estimation Using Observations of Air Concentration and Gamma Dose Rate

by Kasper Skjold Tølløse and Jens Havskov Sørensen

Atmosphere 2022, 13(11), 1877; https://doi.org/10.3390/atmos13111877 - 10 Nov 2022

Cited by 3 | Viewed by 1305

Abstract

In case of a release of hazardous radioactive matter to the atmosphere from e.g., a nuclear power plant accident, atmospheric dispersion models are used to predict the spatial distribution of radioactive particles and gasses. However, at the early stages of an accident, only limited information about the release may be available. Thus, there is a need for source term estimation methods suitable for operational use shortly after an accident. We have developed a Bayesian inverse method for estimating the multi-nuclide source term describing a radioactive release from a nuclear power plant. The method provides a probabilistic source term estimate based on the early available observations of air concentration and gamma dose rate by monitoring systems. The method is intended for operational use in case of a nuclear accident, where no reliable source term estimate exists. We demonstrate how the probabilistic formulation can be used to provide estimates of the released amounts of each radionuclide as well as estimates of future gamma dose rates. The method is applied to an artificial case of a radioactive release from the Loviisa nuclear power plant in southern Finland, considering the most important dose-contributing nuclides. The case demonstrates that only limited air concentration measurement data may be available shortly after the release, and that to a large degree one will have to rely on gamma dose rate observations from a frequently reporting denser monitoring network. Further, we demonstrate that information about the core inventory of the nuclear power plant can be used to constrain the release rates of certain radionuclides, thereby decreasing the number of free parameters of the source term. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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13 pages, 2115 KiB

Open AccessEditor’s ChoiceArticle

Bioaerosol Concentration in a Cattle Feedlot in Neuquén, Argentina

by Marisa Gloria Cogliati, Paula Andrea Paez, Luis Alfredo Pianciola, Marcelo Alejandro Caputo and Paula Natalia Mut

Atmosphere 2022, 13(11), 1761; https://doi.org/10.3390/atmos13111761 - 26 Oct 2022

Cited by 1 | Viewed by 1867

Abstract

There is a global trend toward intensive livestock breeding, which tends to increase the microbial load in the environment as well as the presence of volatile compounds and dust that can cause health issues. Cattle is the major producer of Escherichiacoli (E. coli), a group of foodborne bacteria associated with severe human diseases, and Neuquén province in Argentina has one of the highest rates of uremic hemolytic syndrome incidence in the world. This paper presents the results of two sampling events of E. coli bacteria at 39 sites in La Paisana ranch (LPR), in Añelo (Neuquén), considering locations inside the pens, upwind, and downwind of the feedlot with different time steps, using a Microflow α equipment. The ranch has approximately 600 heads and clean and controlled installations. The field experiment included sampling airborne aerosol deposition and concentration using passive and active methods. Concentrations were also estimated using an atmospheric dispersion model. During the field experiment, counts of up to 2970 CFU/m³ were obtained in the cattle stockyards and up to 111 CFU/m³ at a distance of 100 m. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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Graphical abstract

19 pages, 3328 KiB

Open AccessEditor’s ChoiceArticle

Coupling Effects of Sandstorm and Dust from Coal Bases on the Atmospheric Environment of Northwest China

by Yun Liu, Tingning Zhao, Ruoshui Wang, Xianfeng Ai, Mengwei Wang, Tao Sun and Qunou Jiang

Atmosphere 2022, 13(10), 1629; https://doi.org/10.3390/atmos13101629 - 6 Oct 2022

Cited by 4 | Viewed by 1744

Abstract

The coupling effects of sandstorm and dust from coal bases themselves can have a major impact on the atmospheric environment as well as on human health. The typical coal resource city of Wuhai in Inner Mongolia was selected in order to study these impacts during a severe sandstorm event in March 2021. Particulate matter (PM₁, PM_2.5 and PM₁₀) and total suspended particulate matter (TSP) samples were collected during the sandstorm event of 15–19 March 2021 and non-sandstorm weather (11–13 March 2021) and analyzed for their chemical composition. The concentrations of PM₁, PM_2.5, PM₁₀ and TSP in Wuhai city during the sandstorm were 2.2, 2.6, 4.8 and 6.0 times higher than during non-sandstorm days, respectively. Trace metals concentrations in particles of different sizes generally increased during the sandstorm, while water-soluble ions decreased. Positive matrix fraction (PMF) results showed that the main sources of particles during both sandstorm and non-sandstorm days were industrial emissions, traffic emissions, combustion sources and dust. The proportion of industrial emissions and combustion sources increased compared with non-sandstorm days, while traffic emissions and dust decreased. The backward trajectory analysis results showed that airflows were mainly transported over short distances during non-sandstorm days, and high concentration contribution source areas were from southern Ningxia, southeast Gansu and western Shaanxi. The airflow was mainly transported over long distances during the sandstorm event, and high concentration contribution source areas were from northwestern Inner Mongolia, southern Russia, northern and southwestern Mongolia, and northern Xinjiang. A health risk analysis showed that the risk to human health during sandstorm days related to the chemical composition of particles was generally 1.2–13.1 times higher than during non-sandstorm days. Children were more susceptible to health risks, about 2–6.3 times more vulnerable than adults to the risks from heavy metals in the particles under both weather conditions. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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22 pages, 8634 KiB

Open AccessArticle

Use of Toxic Substance Release Modelling as a Tool for Prevention Planning in Border Areas

by Jozef Kubas, Maria Polorecka, Katarina Holla, Viktor Soltes, Alexander Kelisek, Simeon Strachota and Stanislav Maly

Atmosphere 2022, 13(5), 836; https://doi.org/10.3390/atmos13050836 - 20 May 2022

Cited by 6 | Viewed by 1931

Abstract

The paper deals with the protection of the population and the environment in crisis management and emergency planning. It includes a proposal for an auxiliary tool for crisis managers and commanders to increase the safety of the population and the environment in the evaluated area. The proposal was developed thanks to a detailed analysis of the border area in selected regions of Slovakia, where extraordinary events may occur during the cross-border transport of hazardous substances. The actual outputs are maps of area-border crossings, including the places of transport of hazardous substances specifying a range of possible adverse effects on the endangered area. The modelling process was based on real conditions in the given area. Various scenarios of the possible occurrence of the release of hazardous substances were developed. The scenarios were applied in the ALOHA CAMEO software. Using the software output, it was possible to draw the most probable emergency scenarios with a cross-border effect. Cross-border impacts are crucial challenges in dealing with an emergency, as there is a need to ensure cooperation and coordination of emergency services in two different countries. The outputs proposed by the authors are a tool suitable not only for taking preventive measures but also as an aid in repressive activities. It is, therefore, suitable both for reducing the probability of the occurrence of given emergencies and minimizing its consequences. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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13 pages, 1759 KiB

Open AccessArticle

Simulated Methane Emission Detection Capabilities of Continuous Monitoring Networks in an Oil and Gas Production Region

by Qining Chen, Mrinali Modi, Gary McGaughey, Yosuke Kimura, Elena McDonald-Buller and David T. Allen

Atmosphere 2022, 13(4), 510; https://doi.org/10.3390/atmos13040510 - 23 Mar 2022

Cited by 8 | Viewed by 2970

Abstract

Simulations of the atmospheric dispersion of methane emissions were created for a region containing 26 oil and gas production sites in the Permian Basin in Texas. Virtual methane sensors were placed at 24 of the 26 sites, with at most 1 sensor per site. Continuous and intermittent emissions from each of the 26 oil and gas production sites, over 4 week-long meteorological episodes, representative of winter, spring, summer, and fall meteorology, were simulated. The trade-offs between numbers of sensors and precision of sensors required to reliably detect methane emissions of 1 to 10 kg/h were characterized. A total of 15 sensors, able to detect concentration enhancements of 1 ppm, were capable of identifying emissions at all 26 sites in all 4 week-long meteorological episodes, if emissions were continuous at a rate of 10 kg/h. More sensors or sensors with lower detection thresholds were required if emissions were intermittent or if emission rates were lower. The sensitivity of the required number of sensors to site densities in the region, emission dispersion calculation approaches, meteorological conditions, intermittency of the emissions, and emission rates, were examined. The results consistently indicated that, for the conditions in the Permian Basin, a fixed monitoring network with approximately one continuous monitor per site is likely to be capable of consistently detecting site-level methane emissions in the range of 5–10 kg/h. Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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15 pages, 2765 KiB

Open AccessCommunication

Modelling the Impact of National vs. Local Emission Reduction on PM_2.5 in the West Midlands, UK Using WRF-CMAQ

by Andrea Mazzeo, Jian Zhong, Christina Hood, Stephen Smith, Jenny Stocker, Xiaoming Cai and William J. Bloss

Atmosphere 2022, 13(3), 377; https://doi.org/10.3390/atmos13030377 - 24 Feb 2022

Cited by 11 | Viewed by 2492

Abstract

Ambient air pollution from PM_2.5 is a major risk to human and environmental health, with significant impacts on mortality and morbidity. Mitigation policies—which may be regional or national in extent—need to consider both primary and secondary particles to be effective, balancing within-region emissions and longer-range transport phenomena. The modelling system WRF-CMAQ was used to simulate the impact of emissions reductions in the West Midlands region of the UK, evaluating the change in total PM_2.5 and in its primary and secondary components. Domestic combustion, road transport and agriculture emissions were reduced individually or in combination, at a national or at local level. Combined reduction of road transport and agriculture emissions showed the strongest reduction (29%) in average PM_2.5 if applied at national level. At the local level, reductions from domestic combustion were shown to be the most effective policy (13.4% on average). Secondary inorganic fractions of PM_2.5 are the most abundant, with 25% NO₃⁻ 21% SO₄²⁻ and 13% NH₄⁺ on average. Scenario analysis shows that the contribution of secondary components to the fractional change of PM_2.5 dominates for national policies (up to 0.86 for NO₃⁻) when road transport and agriculture activities are reduced, while at the regional level the elemental and organic carbon fractional changes are dominant (up to 0.64 for organic carbon). Full article

(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications)

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