A classification of no oxidation rates in power plant plumes based on atmospheric conditions

Janssen, L.H.J.M.; Wakeren, J. H. A. van; Duuren, H. Van; Elshout, A.J.

doi:10.1016/0004-6981(88)90298-3

Cited by 30 publications

(9 citation statements)

References 13 publications

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“…The location of the maximum level concentration is substantially the same for the three substances, confirming what also found by other authors (Middleton et al 2007, Janssen 1987). …”

Section: Resultssupporting

confidence: 91%

A Lagrangian particle model with chemical reactions: application in real atmosphere

Alessandrini¹,

Ferrero

2011

IJEP

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Abstract:In this work a lagrangian particle model able to account for simple chemical reactions between NO and O 3 (Alessandrini et al., 2007) has been improved in order to consider the photolysis of NO 2 . A system of chemical equations is numerically solved on an eulerian grid, while the particles trajectories are moved in a lagrangian frame. The NOx emissions of a power plant in real atmosphere, situated in a complex topography environment, have been considered as a test case. The meteorological model RAMS has been applied to build the wind field together with the interface code MIRS to compute turbulence parameters, requested for the dispersion simulations. The plume transitions over an air quality station, allowing for a comparison between the measured and computed concentrations of all the reaction's compounds (NO, NO 2 and O 3 ), have been simulated by the lagrangian particle model. The simulated episodes refer to the diurnal time, when the ultraviolet radiation activates the NO 2 photolysis making necessary the model complete set of chemical equations. In order to reduce computational cost and improve the accuracy of the background O 3 concentration representation, the concept of concentration deficit carried by the particles is proposed and tested. This new method does not need to release a big amount of particles filling the whole domain, but only the inside plume particles should be accounted for. Comparisons between NO/NO 2 's concentrations ratio are presented in term of scatter plots and statistical indexes analysis. The satisfactory results suggest that the model can be used in practical applications in real atmosphere also for regulatory purposes when the NO 2 concentration limits are imposed by the legislation.Key words: Atmospheric dispersion, NO, chemistry model, Lagrangian Particle Model, photo-stationary equilibrium. INTRODUCTIONThe chemical reactions of the pollutants released by a source with the background ambient chemical compounds are a very important task for the air quality and regulatory models; for example when dealing with NO x source and the related photochemical pollution. This aim is generally achieved in the frame of the Eulerian models by considering very complicated chemical schemes, including a large set of reactions and assuming the times scale for turbulence and chemistry such that to allow equilibrium hypothesis (Jacobson, 2001, Griffin et al., 2002, Sokhi et al., 2006. In this way the segregation due to the correlation between the concentration of the chemical compounds is neglected and it is not needed a turbulent model providing these terms. However, in many pollution phenomena, when the time and spatial scales are small, as for example close to the source or in urban environment, this assumption cannot be made and non equilibrium must be considered in order to avoid a too fast reaction rate. The covariance of the concentration should also be known if one had to simulate chemical reactions at small temporal and spatial scales, where the chemical equilibrium is not ye...

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“…The location of the maximum level concentration is substantially the same for the three substances, confirming what also found by other authors (Middleton et al 2007, Janssen 1987). …”

Section: Resultssupporting

confidence: 91%

A Lagrangian particle model with chemical reactions: application in real atmosphere

Alessandrini¹,

Ferrero

2011

IJEP

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“…Therefore, the model is suitable only for predicting concentrations of total NO x , and a subsequent allowance must be made to account for how much of this NO x is in the form of NO 2 at ground level (Janssen et al 1988;Bange et al 1991). Studies have shown that the principal NO x emitted by power station stacks is nitric oxide (NO).…”

Section: Methodsmentioning

confidence: 99%

“…The formation of NO 2 proceeds relatively slowly because the available O 3 is rapidly depleted. Additional O 3 enters the plume as it mixes with the surrounding air to continue the reaction, but this is generally a slow process (Janssen et al 1988). Within 5 km of a source, less than 20% of the NO x is in the form of NO 2 , under stable atmospheric conditions.…”

Section: Methodsmentioning

confidence: 99%

Pollutant Dispersion Modeling

Vawda¹

2003

Handbook of Atmospheric Science

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It is often necessary for operators of industrial processes, developers, or regulatory authorities to quantify the air pollution impact of an existing or proposed scheme (e.g. a power station or a road) for the purposes of licensing or planning. A predictive tool such as an atmospheric dispersion model can be useful in this respect, as it provides a means of calculating air pollution concentrations near ground level in the vicinity of the emitting source, given information about the emissions and the prevailing meteorology. It is the concentration of the pollutant near ground level that is important in determining whether there are any potential ill effects, e.g. on human health; air quality standards and guidelines are set in terms of concentration values, not source rates.The aim of this chapter is to provide details on what types of model are available, how they should be used, and their limitations. The information required to run dispersion models, the type of results that are produced, and how these can be interpreted are described. The case studies illustrate how the results of various dispersion models can be used in an air quality assessment and highlight some of the problems that are encountered in the modeling approach. A detailed technical description of the theory of atmospheric dispersion is provided in Chapter 10.Dispersion models take a number of forms, from simple nomograms and spreadsheets to sophisticated computer programs. It is important that the model is appropriate for the complexity of the study (DoE 1995a). Factors such as model accuracy and validation need to be taken into account (see Case study 5). It is also important to assess the availability of both meteorological and emissions data; some models do not require detailed meteorological data because they make broad assumptions about the prevailing local climate, while others may require quite detailed information on meteorology and emissions. EMISSION SOURCES RECOGNIZED BY ATMOSPHERIC DISPERSION MODELSThe three main sources of air pollution modeled are:1 Emissions from vehicle exhausts on roads, which generally make the greatest contribution to air pollution in urban areas.2 Controlled industrial, commercial, and domestic emissions from chimneys. 3 Fugitive emissions (e.g. leakages from industrial plant, or particulate matter from mineral extraction schemes; see Chapter 9). These sources may be divided into three main categories that are recognized by dispersion models: 1 Point sources. These are individual chimneys. The simpler models can treat only one stack at a time (EA 1998), though more sophisticated

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“…Most of NO released from traffic is oxidised to NO 2 within a time scale of a few minutes [20], while for stationary releases, this time scale is of the order of 10-20 min [18,20]. Far from the sources, an approximate photochemical equilibrium is reached, resulting in a NO 2 /NO x ratio of about 90% [20].…”

Section: Application To Buenos Aires Citymentioning

confidence: 97%

Design of an Air-Quality Surveillance System for Buenos Aires City Integrated by a NO x Monitoring Network and Atmospheric Dispersion Models

Mazzeo

Venegas

2007

Environ Model Assess

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This paper presents an air-quality surveillance system designed to detect the occurrence of air pollutant concentrations greater than a reference level in an urban area. The system is integrated by an air-quality monitoring network and atmospheric dispersion models simulations. An objective methodology to design an urban air-quality monitoring network is proposed. This methodology is based on the analysis of air-quality modelling results. The procedure is applied to design an air-quality monitoring network to control NO x concentration levels in Buenos Aires City. Results indicate that six monitors will detect the occurrence of concentration greater than the air-quality guidelines with an efficiency of about 67%. Once a violation is detected, results of atmospheric dispersion models will help in the determination of affected areas. Four possible examples are included to illustrate the assistance that the results of atmospheric dispersion models can bring to a better estimation of possible affected areas in the city. Combining these results with the last census data, an estimation of the inhabitants possibly exposed is obtained.

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A classification of no oxidation rates in power plant plumes based on atmospheric conditions

Cited by 30 publications

References 13 publications

A Lagrangian particle model with chemical reactions: application in real atmosphere

A Lagrangian particle model with chemical reactions: application in real atmosphere

Pollutant Dispersion Modeling

Design of an Air-Quality Surveillance System for Buenos Aires City Integrated by a NO x Monitoring Network and Atmospheric Dispersion Models

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