Comparison of plume lateral dispersion coefficients schemes: Effect of averaging time

Hoinaski, Leonardo; Franco, Daniel; Lisboa, Henrique de Melo

doi:10.1016/j.apr.2015.08.004

Cited by 10 publications

(6 citation statements)

References 25 publications

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“…According to Hoinaski et al [32], the methods of lateral dispersion coefficients employed on AERMOD and CALPUFF reached a strong correlation with observed maximum concentrations and lateral dispersion. However, their estimates are biased and the magnitude of systematic errors tend to grow as the averaging time decreases.…”

Section: Resultsmentioning

confidence: 93%

“…Therefore, both models share a weakness: the inability to calculate short-term time averages, as in the case of flammability, malodour nuisance and, often, toxicity [4,5]. According to Hoinaski et al [32], the methods of lateral dispersion coefficients employed on AERMOD and CALPUFF reached a strong correlation with observed maximum concentrations and lateral dispersion. However, their estimates are biased and the magnitude of systematic errors tend to grow as the averaging time decreases.…”

Section: Resultsmentioning

confidence: 96%

“…As this fluctuation has little influence in terms of reducing average times, it is possible that the addition of this effect by AERMOD increased the value of σ and was the reason for overestimations at 30-second averaging time (Table 2). A further investigation of discrepancies increase with distance can be found in Hoinaski et al [32] Downloaded by [University of Sussex Library] at 15:22 27 June 2016 Table 3 shows the performance of AERMOD in the estimation of σ in average times of 10 seconds and one minute compared to observations of sonic anemometer. Table 4 shows statistical indexes from the comparison among observations and estimates of σ .…”

Section: Aermod Performance In Round Hill II Experimentsmentioning

confidence: 96%

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An analysis of error propagation in AERMOD lateral dispersion using Round Hill II and Uttenweiller experiments in reduced averaging times

Hoinaski

Franco

Lisboa

2016

Environmental Technology

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Dispersion modelling was proved by researchers that most part of the models, including the regulatory models recommended by the Environmental Protection Agency of the United States (AERMOD and CALPUFF), do not have the ability to predict under complex situations. This article presents a novel evaluation of the propagation of errors in lateral dispersion coefficient of AERMOD with emphasis on estimate of average times under 10 min. The sources of uncertainty evaluated were parameterizations of lateral dispersion ([Formula: see text]), standard deviation of lateral wind speed ([Formula: see text]) and processing of obstacle effect. The model's performance was tested in two field tracer experiments: Round Hill II and Uttenweiller. The results show that error propagation from the estimate of [Formula: see text] directly affects the determination of [Formula: see text], especially in Round Hill II experiment conditions. After average times are reduced, errors arise in the parameterization of [Formula: see text], even after observation assimilations of [Formula: see text], exposing errors on Lagrangian Time Scale parameterization. The assessment of the model in the presence of obstacles shows that the implementation of a plume rise model enhancement algorithm can improve the performance of the AERMOD model. However, these improvements are small when the obstacles have a complex geometry, such as Uttenweiller.

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Section: Resultsmentioning

confidence: 93%

Section: Resultsmentioning

confidence: 96%

Section: Aermod Performance In Round Hill II Experimentsmentioning

confidence: 96%

See 1 more Smart Citation

An analysis of error propagation in AERMOD lateral dispersion using Round Hill II and Uttenweiller experiments in reduced averaging times

Hoinaski

Franco

Lisboa

2016

Environmental Technology

Self Cite

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“…The Gaussian model of impurities dispersion underlies IAEA procedures [22], which set out recommendations for determining dispersions based on input meteorological parameters and for performing calculations on emission dissipation after accidents at nuclear power plants. The model is characterized by a straight cloud trajectory and is intended for express accident assessments at relatively short distances [23].…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…That suite simulates the propagation of a dangerous substance using the Gaussian model of admixture dispersion [26] ac-cording to the parameters introduced and makes it possible to visualize the results of forecasting. However, the approaches reported in [20][21][22][23][24][25][26] do not take into consideration the deposition of a cloud of dangerous gases by operational and rescue units.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Devising a procedure to forecast the level of chemical damage to the atmosphere during active deposition of dangerous gases

Melnychenko

Kustov

Basmanov

et al. 2022

EEJET

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This paper reports a procedure devised to forecast the level of chemical pollution of the atmosphere, which includes a mathematical model for the distribution of the concentration of dangerous gas in the atmosphere at its active deposition by dispersed jets of liquid, as well as a technique for its implementation. Based on the differential equations of gas distribution in space, a phased model of the propagation of a cloud of a dangerous chemical substance was built. The model describes stages in the discharge of a dangerous gaseous substance from emergency technological equipment, the deposition of dangerous gas by a finely-dispersed flow, and free propagation of the cloud in the air. The reported mathematical model makes it possible to calculate the size of pollution zones while determining the boundary safety conditions. When forecasting, the main meteorological parameters, the width of the deposition zone, and the chemical properties of both the gas and liquid are taken into consideration. The comparative analysis of the results of forecasting a conditional zone of chemical damage with the free propagation of the cloud, and at the active deposition by precipitation or technical devices, was carried out. The simulation results revealed that with an increase in the wind speed from 1 m/s to 5 m/s, the size of the affected area increases by 2.7 times, while the concentration of dangerous gas in the cloud falls by 2.5‒3 times. An algorithm has been proposed for integrating the devised methodology of forecasting the level of chemical pollution of the atmosphere into a general cycle of emergency management. It should be especially noted that the devised procedure contains the entire range of components that are necessary for its practical application. It includes a description of the procedure and practical recommendations for the use of the proposed technique in the elimination of emergencies, as well as a list of probable events when the use of the developed procedure would be most effective.

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Near‐field atmospheric inversions for the localization and quantification of controlled methane releases using stationary and mobile measurements

Kumar

Broquet

Caldow

et al. 2022

Quart J Royal Meteoro Soc

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This study evaluates two local‐scale atmospheric inversion approaches for the monitoring of methane (CH4) emissions from industrial sites based on in situ atmospheric CH4 mole fraction measurements from stationary or mobile sensors. We participated in a two‐week campaign of CH4 controlled‐release experiments at TotalEnergies Anomaly Detection Initiatives (TADI) in Lacq, France in October 2019. We analyzed releases from various points within a 40 m × 50 m area with constant rates of 0.16 to 30 g CH4 s−1 over 25 to 75 mins, using fixed‐point and mobile measurements, and testing different inversion configurations with a Gaussian dispersion model. An inlet switching system, combining a limited number (6–7) of high‐precision gas analyzers with a higher number (16) of sampling lines, ensured that a sufficient number of fixed measurement points sampled the plume downwind of the sources and the background mole fractions for any wind direction. The inversions using these fixed‐point measurements provide release rate estimates with approximately 23%–30% average errors and estimates of the location of the releases with approximately 8–10 m average errors. The inversions using the mobile measurements provide estimates with approximately 20%–30% average errors for the release rates and approximately 30 m average errors for the release locations. The precision of the release rate estimates from both inversion frameworks corresponds to the best estimation precision documented on site‐scale CH4 inversions. However, the use of continuous measurements from fixed stations provides much more robust estimates of the source locations than that of the mobile measurements.

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Comparison of plume lateral dispersion coefficients schemes: Effect of averaging time

Cited by 10 publications

References 25 publications

An analysis of error propagation in AERMOD lateral dispersion using Round Hill II and Uttenweiller experiments in reduced averaging times

An analysis of error propagation in AERMOD lateral dispersion using Round Hill II and Uttenweiller experiments in reduced averaging times

Devising a procedure to forecast the level of chemical damage to the atmosphere during active deposition of dangerous gases

Near‐field atmospheric inversions for the localization and quantification of controlled methane releases using stationary and mobile measurements

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