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Open AccessArticle

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

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Atmosphere 2023, 14(3), 508; https://doi.org/10.3390/atmos14030508 - 06 Mar 2023

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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 [...] Read more.

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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Open AccessArticle

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

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

Viewed by 481

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, [...] Read more.

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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Open AccessArticle

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

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Kasper Skjold Tølløse

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Jens Havskov Sørensen

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

Viewed by 608

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 [...] Read more.

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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Open AccessEditor’s ChoiceArticle

Bioaerosol Concentration in a Cattle Feedlot in Neuquén, Argentina

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Marisa Gloria Cogliati

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Paula Andrea Paez

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Luis Alfredo Pianciola

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Marcelo Alejandro Caputo

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Paula Natalia Mut

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

Viewed by 741

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 ( [...] Read more.

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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Open AccessEditor’s ChoiceArticle

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

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Atmosphere 2022, 13(10), 1629; https://doi.org/10.3390/atmos13101629 - 06 Oct 2022

Viewed by 758

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 [...] Read more.

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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Open AccessArticle

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

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

Cited by 1 | Viewed by 904

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 [...] Read more.

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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Open AccessArticle

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

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Elena McDonald-Buller

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David T. Allen

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

Cited by 3 | Viewed by 1681

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 [...] Read more.

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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Open AccessCommunication

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

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

Cited by 4 | Viewed by 1331

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 [...] Read more.

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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