Atmospheric dispersion modeling

Atmospheric dispersion modeling is the mathematical simulation of how air pollutants disperse in the ambient atmosphere. It is performed with computer programs that include algorithms to solve the mathematical equations that govern the pollutant dispersion. The dispersion models are used to estimate the downwind ambient concentration of air pollutants or toxins emitted from sources such as industrial plants, vehicular traffic or accidental chemical releases. They can also be used to predict future concentrations under specific scenarios (i.e. changes in emission sources). Therefore, they are the dominant type of model used in air quality policy making. They are most useful for pollutants that are dispersed over large distances and that may react in the atmosphere. For pollutants that have a very high spatio-temporal variability (i.e. have very steep distance to source decay such as black carbon) and for epidemiological studies statistical land-use regression models are also used.

Dispersion models are important to governmental agencies tasked with protecting and managing the ambient air quality. The models are typically employed to determine whether existing or proposed new industrial facilities are or will be in compliance with the National Ambient Air Quality Standards (NAAQS) in the United States and other nations. The models also serve to assist in the design of effective control strategies to reduce emissions of harmful air pollutants. During the late 1960s, the Air Pollution Control Office of the U.S. EPA initiated research projects that would lead to the development of models for the use by urban and transportation planners.[1] A major and significant application of a roadway dispersion model that resulted from such research was applied to the Spadina Expressway of Canada in 1971.

Air dispersion models are also used by public safety responders and emergency management personnel for emergency planning of accidental chemical releases. Models are used to determine the consequences of accidental releases of hazardous or toxic materials, Accidental releases may result in fires, spills or explosions that involve hazardous materials, such as chemicals or radionuclides. The results of dispersion modeling, using worst case accidental release source terms and meteorological conditions, can provide an estimate of location impacted areas, ambient concentrations, and be used to determine protective actions appropriate in the event a release occurs. Appropriate protective actions may include evacuation or shelter in place for persons in the downwind direction. At industrial facilities, this type of consequence assessment or emergency planning is required under the Clean Air Act (United States) (CAA) codified in Part 68 of Title 40 of the Code of Federal Regulations.

The dispersion models vary depending on the mathematics used to develop the model, but all require the input of data that may include:

  • Meteorological conditions such as wind speed and direction, the amount of atmospheric turbulence (as characterized by what is called the "stability class"), the ambient air temperature, the height to the bottom of any inversion aloft that may be present, cloud cover and solar radiation.
  • Source term (the concentration or quantity of toxins in emission or accidental release source terms) and temperature of the material
  • Emissions or release parameters such as source location and height, type of source (i.e., fire, pool or vent stack)and exit velocity, exit temperature and mass flow rate or release rate.
  • Terrain elevations at the source location and at the receptor location(s), such as nearby homes, schools, businesses and hospitals.
  • The location, height and width of any obstructions (such as buildings or other structures) in the path of the emitted gaseous plume, surface roughness or the use of a more generic parameter "rural" or "city" terrain.

Many of the modern, advanced dispersion modeling programs include a pre-processor module for the input of meteorological and other data, and many also include a post-processor module for graphing the output data and/or plotting the area impacted by the air pollutants on maps. The plots of areas impacted may also include isopleths showing areas of minimal to high concentrations that define areas of the highest health risk. The isopleths plots are useful in determining protective actions for the public and responders.

The atmospheric dispersion models are also known as atmospheric diffusion models, air dispersion models, air quality models, and air pollution dispersion models.

AirPollutionSource
Industrial air pollution source

Atmospheric layers

Discussion of the layers in the Earth's atmosphere is needed to understand where airborne pollutants disperse in the atmosphere. The layer closest to the Earth's surface is known as the troposphere. It extends from sea-level to a height of about 18 km and contains about 80 percent of the mass of the overall atmosphere. The stratosphere is the next layer and extends from 18 km to about 50 km. The third layer is the mesosphere which extends from 50 km to about 80 km. There are other layers above 80 km, but they are insignificant with respect to atmospheric dispersion modeling.

The lowest part of the troposphere is called the atmospheric boundary layer (ABL) or the planetary boundary layer (PBL) . The air temperature of the atmosphere decreases with increasing altitude until it reaches what is called an inversion layer (where the temperature increases with increasing altitude) that caps the Convective Boundary Layer, typically to about 1.5 to 2.0 km in height. The upper part of the troposphere (i.e., above the inversion layer) is called the free troposphere and it extends up to the tropopause (the boundary in the Earth's atmosphere between the troposphere and the stratosphere). In tropical and mid-latitudes during daytime, the Free convective layer can comprise the entire troposphere, which is up to 10 km to 18 km in the Intertropical convergence zone.

The ABL is of the most important with respect to the emission, transport and dispersion of airborne pollutants. The part of the ABL between the Earth's surface and the bottom of the inversion layer is known as the mixing layer. Almost all of the airborne pollutants emitted into the ambient atmosphere are transported and dispersed within the mixing layer. Some of the emissions penetrate the inversion layer and enter the free troposphere above the ABL.

In summary, the layers of the Earth's atmosphere from the surface of the ground upwards are: the ABL made up of the mixing layer capped by the inversion layer; the free troposphere; the stratosphere; the mesosphere and others. Many atmospheric dispersion models are referred to as boundary layer models because they mainly model air pollutant dispersion within the ABL. To avoid confusion, models referred to as mesoscale models have dispersion modeling capabilities that extend horizontally up to a few hundred kilometres. It does not mean that they model dispersion in the mesosphere.

Gaussian air pollutant dispersion equation

The technical literature on air pollution dispersion is quite extensive and dates back to the 1930s and earlier. One of the early air pollutant plume dispersion equations was derived by Bosanquet and Pearson.[2] Their equation did not assume Gaussian distribution nor did it include the effect of ground reflection of the pollutant plume.

Sir Graham Sutton derived an air pollutant plume dispersion equation in 1947[3] which did include the assumption of Gaussian distribution for the vertical and crosswind dispersion of the plume and also included the effect of ground reflection of the plume.

Under the stimulus provided by the advent of stringent environmental control regulations, there was an immense growth in the use of air pollutant plume dispersion calculations between the late 1960s and today. A great many computer programs for calculating the dispersion of air pollutant emissions were developed during that period of time and they were called "air dispersion models". The basis for most of those models was the Complete Equation For Gaussian Dispersion Modeling Of Continuous, Buoyant Air Pollution Plumes shown below:[4][5]

where:  
= crosswind dispersion parameter
  =
= vertical dispersion parameter =
= vertical dispersion with no reflections
  =
= vertical dispersion for reflection from the ground
  =
= vertical dispersion for reflection from an inversion aloft
  =
         
         
         
= concentration of emissions, in g/m³, at any receptor located:
            x meters downwind from the emission source point
            y meters crosswind from the emission plume centerline
            z meters above ground level
= source pollutant emission rate, in g/s
= horizontal wind velocity along the plume centerline, m/s
= height of emission plume centerline above ground level, in m
= vertical standard deviation of the emission distribution, in m
= horizontal standard deviation of the emission distribution, in m
= height from ground level to bottom of the inversion aloft, in m
= the exponential function

The above equation not only includes upward reflection from the ground, it also includes downward reflection from the bottom of any inversion lid present in the atmosphere.

The sum of the four exponential terms in converges to a final value quite rapidly. For most cases, the summation of the series with m = 1, m = 2 and m = 3 will provide an adequate solution.

and are functions of the atmospheric stability class (i.e., a measure of the turbulence in the ambient atmosphere) and of the downwind distance to the receptor. The two most important variables affecting the degree of pollutant emission dispersion obtained are the height of the emission source point and the degree of atmospheric turbulence. The more turbulence, the better the degree of dispersion.

Equations[6][7] for and are:

(x) = exp(Iy + Jyln(x) + Ky[ln(x)]2)

(x) = exp(Iz + Jzln(x) + Kz[ln(x)]2)

(units of , and , and x are in meters)

Coefficient A B C D E F
Ry 0.443 0.324 0.216 0.141 0.105 0.071
ry 0.894 0.894 0.894 0.894 0.894 0.894
Iy -1.104 -1.634 -2.054 -2.555 -2.754 -3.143
Jy 0.9878 1.0350 1.0231 1.0423 1.0106 1.0148
Ky -0.0076 -0.0096 -0.0076 -0.0087 -0.0064 -0.0070
Iz 4.679 -1.999 -2.341 -3.186 -3.783 -4.490
Jz -1.7172 0.8752 0.9477 1.1737 1.3010 1.4024
Kz 0.2770 0.0136 -0.0020 -0.0316 -0.0450 -0.0540

The classification of stability class is proposed by F. Pasquill.[8] The six stability classes are referred to: A-extremely unstable B-moderately unstable C-slightly unstable D-neutral E-slightly stable F-moderately stable

The resulting calculations for air pollutant concentrations are often expressed as an air pollutant concentration contour map in order to show the spatial variation in contaminant levels over a wide area under study. In this way the contour lines can overlay sensitive receptor locations and reveal the spatial relationship of air pollutants to areas of interest.

Whereas older models rely on stability classes (see air pollution dispersion terminology) for the determination of and , more recent models increasingly rely on the Monin-Obukhov similarity theory to derive these parameters.

Briggs plume rise equations

The Gaussian air pollutant dispersion equation (discussed above) requires the input of H which is the pollutant plume's centerline height above ground level—and H is the sum of Hs (the actual physical height of the pollutant plume's emission source point) plus ΔH (the plume rise due the plume's buoyancy).

Gaussian Plume (SVG)
Visualization of a buoyant Gaussian air pollutant dispersion plume

To determine ΔH, many if not most of the air dispersion models developed between the late 1960s and the early 2000s used what are known as "the Briggs equations." G.A. Briggs first published his plume rise observations and comparisons in 1965.[9] In 1968, at a symposium sponsored by CONCAWE (a Dutch organization), he compared many of the plume rise models then available in the literature.[10] In that same year, Briggs also wrote the section of the publication edited by Slade[11] dealing with the comparative analyses of plume rise models. That was followed in 1969 by his classical critical review of the entire plume rise literature,[12] in which he proposed a set of plume rise equations which have become widely known as "the Briggs equations". Subsequently, Briggs modified his 1969 plume rise equations in 1971 and in 1972.[13][14]

Briggs divided air pollution plumes into these four general categories:

  • Cold jet plumes in calm ambient air conditions
  • Cold jet plumes in windy ambient air conditions
  • Hot, buoyant plumes in calm ambient air conditions
  • Hot, buoyant plumes in windy ambient air conditions

Briggs considered the trajectory of cold jet plumes to be dominated by their initial velocity momentum, and the trajectory of hot, buoyant plumes to be dominated by their buoyant momentum to the extent that their initial velocity momentum was relatively unimportant. Although Briggs proposed plume rise equations for each of the above plume categories, it is important to emphasize that "the Briggs equations" which become widely used are those that he proposed for bent-over, hot buoyant plumes.

In general, Briggs's equations for bent-over, hot buoyant plumes are based on observations and data involving plumes from typical combustion sources such as the flue gas stacks from steam-generating boilers burning fossil fuels in large power plants. Therefore, the stack exit velocities were probably in the range of 20 to 100 ft/s (6 to 30 m/s) with exit temperatures ranging from 250 to 500 °F (120 to 260 °C).

A logic diagram for using the Briggs equations[4] to obtain the plume rise trajectory of bent-over buoyant plumes is presented below:

BriggsLogic
where:  
Δh = plume rise, in m
F  = buoyancy factor, in m4s−3
x = downwind distance from plume source, in m
xf = downwind distance from plume source to point of maximum plume rise, in m
u = windspeed at actual stack height, in m/s
s  = stability parameter, in s−2

The above parameters used in the Briggs' equations are discussed in Beychok's book.[4]

See also

Atmospheric dispersion models

List of atmospheric dispersion models provides a more comprehensive list of models than listed below. It includes a very brief description of each model.

HYSPLITTrajectoriesforNewportStateParkpage72
2016 HYSPLIT map

Organizations

Others

References

  1. ^ Fensterstock, J.C. et al., "Reduction of air pollution potential through environmental planning", JAPCA, Vol.21, No.7, 1971.
  2. ^ Bosanquet, C.H. and Pearson, J.L., "The spread of smoke and gases from chimneys", Trans. Faraday Soc., 32:1249, 1936
  3. ^ Sutton, O.G., "The problem of diffusion in the lower atmosphere", QJRMS, 73:257, 1947 and "The theoretical distribution of airborne pollution from factory chimneys", QJRMS, 73:426, 1947
  4. ^ a b c Beychok, Milton R. (2005). Fundamentals Of Stack Gas Dispersion (4th ed.). author-published. ISBN 0-9644588-0-2.
  5. ^ Turner, D.B. (1994). Workbook of atmospheric dispersion estimates: an introduction to dispersion modeling (2nd ed.). CRC Press. ISBN 1-56670-023-X.
  6. ^ Seinfeld, John H. (2006). Atmospheric chemistry and physics: from air pollution to climate change. Chapter 18: Wiley. ISBN 9780471720171.
  7. ^ Hanna, Steven (1982). "Handbook on Atmospheric Diffusion". U.S. Department of Energy Report.
  8. ^ W, Klug (April 1984). Atmospheric Diffusion (3rd Edition). F. Pasquill and F. B. Smith. Ellis Horwood, (John Wiley & Sons) Chichester, 1983 (3rd ed.). New York: Quarterly Journal of the Royal Meteorological Society.
  9. ^ Briggs, G.A., "A plume rise model compared with observations", JAPCA, 15:433–438, 1965
  10. ^ Briggs, G.A., "CONCAWE meeting: discussion of the comparative consequences of different plume rise formulas", Atmos. Envir., 2:228–232, 1968
  11. ^ Slade, D.H. (editor), "Meteorology and atomic energy 1968", Air Resources Laboratory, U.S. Dept. of Commerce, 1968
  12. ^ Briggs, G.A., "Plume Rise", USAEC Critical Review Series, 1969
  13. ^ Briggs, G.A., "Some recent analyses of plume rise observation", Proc. Second Internat'l. Clean Air Congress, Academic Press, New York, 1971
  14. ^ Briggs, G.A., "Discussion: chimney plumes in neutral and stable surroundings", Atmos. Envir., 6:507–510, 1972

Further reading

Books

Introductory
  • Beychok, Milton R. (2005). Fundamentals Of Stack Gas Dispersion (4th ed.). author-published. ISBN 0-9644588-0-2.
  • Center for Chemical Process Safety (1999). Guidelines for Chemical Process Quantitative Risk Analysis (2nd ed.). American Institute of Chemical Engineers, New York, NY. ISBN 978-0-8169-0720-5.
  • Center for Chemical Process Safety (1996). Guidelines for Use of Vapor Cloud and Source Dispersion Models, with Worked Examples (2nd ed.). American Institute of Chemical Engineers, New York, NY. ISBN 978-0-8169-0702-1.
  • Schnelle, Karl B. & Dey, Partha R. (1999). Atmospheric Dispersion Modeling Compliance Guide (1st ed.). McGraw-Hill Professional. ISBN 0-07-058059-6.
  • Turner, D.B. (1994). Workbook of Atmospheric Dispersion Estimates: An Introduction to Dispersion Modeling (2nd ed.). CRC Press. ISBN 1-56670-023-X.
Advanced
  • Arya, S. Pal (1998). Air Pollution Meteorology and Dispersion (1st ed.). Oxford University Press. ISBN 0-19-507398-3.
  • Barrat, Rod (2001). Atmospheric Dispersion Modelling (1st ed.). Earthscan Publications. ISBN 1-85383-642-7.
  • Colls, Jeremy (2002). Air Pollution (1st ed.). Spon Press (UK). ISBN 0-415-25565-1.
  • Cooper JR, Randle K, Sokh RG (2003). Radioactive Releases in the Environment (1st ed.). John Wiley & Sons. ISBN 0-471-89924-0.
  • European Process Safety Centre (1999). Atmospheric Dispersion (1st ed.). Rugby: Institution of Chemical Engineers. ISBN 0-85295-404-2.
  • Godish, Thad (2003). Air Quality (4th ed.). CRC Press. ISBN 1-56670-586-X.
  • Hanna, S.R. & Drivas, D. G. (1996). Guidelines for Use of Vapor Cloud Dispersion Models (2nd ed.). Wiley-American Institute of Chemical Engineers. ISBN 0-8169-0702-1.
  • Hanna, S. R. & Strimaitis, D. G. (1989). Workbook of Test Cases for Vapor Cloud Source Dispersion Models (1st ed.). Center for Chemical Process Safety, American Institute of Chemical Engineers. ISBN 0-8169-0455-3.
  • Hanna, S. R. & Britter, R.E. (2002). Wind Flow and Vapor Cloud Dispersion at Industrial and Urban Sites (1st ed.). Wiley-American Institute of Chemical Engineers. ISBN 0-8169-0863-X.
  • Perianez, Raul (2005). Modelling the dispersion of radionuclides in the marine environment : an introduction (1st ed.). Springer. ISBN 3-540-24875-7.
  • Pielke, Roger A. (2001). Mesoscale Modeling (2nd ed.). Elsevier. ISBN 0-12-554766-8.
  • Zannetti, P. (1990). Air pollution modeling : theories, computational methods, and available software. Van Nostrand Reinhold. ISBN 0-442-30805-1.

Proceedings

  • Forago I, Georgiev K, Havasi A, eds. (2004). Advances in Air Pollution Modeling for Environmental Security (NATO Workshop). Springer, 2005. ISSN 0957-4352.
  • Kretzschmar JG, Cosemans G, eds. (1996). Harmonization within atmospheric dispersion modelling for regulatory purposes (4th Workshop). International Journal of Environment and Pollution, vol. 8 no. 3–6, Interscience Enterprises, 1997. ISSN 0957-4352.
  • Bartzis, J G., ed. (1998). Harmonization within atmospheric dispersion modelling for regulatory purposes (5th Workshop). International Journal of Environment and Pollution, vol. 14 no. 1–6, Interscience Enterprises, 2000. ISSN 0957-4352.
  • Coppalle, A., ed. (1999). Harmonization within atmospheric dispersion modelling for regulatory purposes (6th Workshop). International Journal of Environment and Pollution, vol. 16 no. 1–6, Inderscience Enterprises, 2001. ISSN 0957-4352.
  • Batchvarova, E., ed. (2002). Harmonization within atmospheric dispersion modelling for regulatory purposes (8th Workshop). International Journal of Environment and Pollution, vol. 20 no. 1–6, Inderscience Enterprises, 2003. ISSN 0957-4352.
  • Suppan, P., ed. (2004). Harmonization within atmospheric dispersion modelling for regulatory purposes (8th Workshop). International Journal of Environment and Pollution, vol. 24 no. 1–6 and vol.25 no. 1–6, Inderscience Enterprises, 2005. ISSN 0957-4352.
  • Zannetti, P., ed. (1993). International Conference on Air Pollution (1st, Mexico City). Computational Mechanics, 1993. ISBN 1-56252-146-2.
  • De Wispelaere, C., ed. (1980). International Technical Meeting on Air Pollution Modeling and Its Application (11th). Plenum Press, 1981. ISBN 0-306-40820-1.
  • De Wispelaere, C., ed. (1982). International Technical Meeting on Air Pollution Modeling and Its Application (13th). NATO Committee on the Challenges of Modern Society [by] Plenum Press, 1984. ISBN 0-306-41491-0.
  • Gryning, S.; Schiermeir, F.A., eds. (1995). International Technical Meeting on Air Pollution Modeling and Its Application (21st). NATO Committee on the Challenges of Modern Society [by] Plenum Press, 1996. ISBN 0-306-45381-9.
  • Gryning, S.; Chaumerliac, N., eds. (1997). International Technical Meeting on Air Pollution Modeling and Its Application (22nd). NATO Committee on the Challenges of Modern Society [by] Plenum Press, 1998. ISBN 0-306-45821-7.
  • Gryning, S.; Batchvarova, E., eds. (1998). International Technical Meeting on Air Pollution Modeling and Its Application (23rd). NATO Committee on the Challenges of Modern Society [by] Kluwer Academic/Plenum Press, 2000. ISBN 0-306-46188-9.
  • Gryning, S.; Schiermeir, F.A., eds. (2000). International Technical Meeting on Air Pollution Modeling and Its Application (24th). NATO Committee on the Challenges of Modern Society [by] Kluwer Academic, 2001. ISBN 0-306-46534-5.
  • :Borrego, C.; Schayes, G., eds. (2000). International Technical Meeting on Air Pollution Modeling and Its Application (25th). NATO Committee on the Challenges of Modern Society [by] Kluwer Academic, 2002. ISBN 0-306-47294-5.
  • Borrego, C.; Incecik, S., eds. (2003). International Technical Meeting on Air Pollution Modeling and Its Application (26th). NATO Committee on the Challenges of Modern Society [by] Kluwer Academic/Plenum Press, 2004. ISBN 0-306-48464-1.
  • Committee on the Atmospheric Dispersion of Hazardous Material Releases, National Research Council, ed. (2002). Tracking and Predicting the Atmospheric Dispersion of Hazardous Material Releases (Workshop). National Academies Press, 2003. ISBN 0-309-08926-3.

Guidance

External links

ADMS 3

The ADMS 3 (Atmospheric Dispersion Modelling System) is an advanced atmospheric pollution dispersion model for calculating concentrations of atmospheric pollutants emitted both continuously from point, line, volume and area sources, or intermittently from point sources. It was developed by Cambridge Environmental Research Consultants (CERC) of the UK in collaboration with the UK Meteorological Office, National Power plc (now INNOGY Holdings plc) and the University of Surrey. The first version of ADMS was released in 1993. The version of the ADMS model discussed on this page is version 3 and was released in February 1999. It runs on Microsoft Windows. The current release, ADMS 5 Service Pack 1, was released in April 2013 with a number of additional features.

AERMOD

The AERMOD atmospheric dispersion modeling system is an integrated system that includes three modules:

A steady-state dispersion model designed for short-range (up to 50 kilometers) dispersion of air pollutant emissions from stationary industrial sources.

A meteorological data preprocessor (AERMET) that accepts surface meteorological data, upper air soundings, and optionally, data from on-site instrument towers. It then calculates atmospheric parameters needed by the dispersion model, such as atmospheric turbulence characteristics, mixing heights, friction velocity, Monin-Obukov length and surface heat flux.

A terrain preprocessor (AERMAP) whose main purpose is to provide a physical relationship between terrain features and the behavior of air pollution plumes. It generates location and height data for each receptor location. It also provides information that allows the dispersion model to simulate the effects of air flowing over hills or splitting to flow around hills.AERMOD also includes PRIME (Plume Rise Model Enhancements) which is an algorithm for modeling the effects of downwash created by the pollution plume flowing over nearby buildings.

ATSTEP

ATSTEP is a Gaussian puff model for diagnosis and prognosis of the atmospheric dispersion, deposition, gamma radiation and doses of released radioactivity in case of accidents in nuclear power plants or during transport, and from dirty bombs.

It was developed by Forschungszentrum Karlsruhe (now Karlsruhe Institute of Technology, KIT), one of the largest national research centers in Germany, and is designed for running in the RODOS (Real-time On-line DecisiOn Support) system for nuclear emergency management. RODOS is operational at the German Federal Office for Radiation Protection (BfS), and test operational in many other European countries. More information on RODOS is available on the RODOS website here and on the ATSTEP model here.

AUSTAL2000

Austal2000 is an atmospheric dispersion model for simulating the dispersion of air pollutants in the ambient atmosphere. It was developed by Ingenieurbüro Janicke in Dunum, Germany under contract to the Federal Ministry for Environment, Nature Conservation and Nuclear Safety.

Although not named in the TA Luft, it is the reference dispersion model accepted as being in compliance with the requirements of Annex 3 of the TA Luft and the pertinent VDI Guidelines.

CALPUFF

CALPUFF is an advanced, integrated Lagrangian puff modeling system for the simulation of atmospheric pollution dispersion distributed by the Atmospheric Studies Group at TRC Solutions.It is maintained by the model developers and distributed by TRC.

The model has been adopted by the United States Environmental Protection Agency (EPA) in its Guideline on Air Quality Models as a preferred model for assessing long range transport of pollutants and their impacts on Federal Class I areas and on a case-by-case basis for certain near-field applications involving complex meteorological conditions.

The integrated modeling system consists of three main components and a set of preprocessing and postprocessing programs. The main components of the modeling system are CALMET (a diagnostic 3-dimensional meteorological model), CALPUFF (an air quality dispersion model), and CALPOST (a postprocessing package). Each of these programs has a graphical user interface (GUI). In addition to these components, there are numerous other processors that may be used to prepare geophysical (land use and terrain) data in many standard formats, meteorological data (surface, upper air, precipitation, and buoy data), and interfaces to other models such as the Penn State/NCAR Mesoscale Model (MM5), the National Centers for Environmental Prediction (NCEP) Eta model and the RAMS meteorological model.

The CALPUFF model is designed to simulate the dispersion of buoyant, puff or continuous point and area pollution sources as well as the dispersion of buoyant, continuous line sources. The model also includes algorithms for handling the effect of downwash by nearby buildings in the path of the pollution plumes.

Czech Hydrometeorological Institute

The Czech Hydrometeorological Institute (CHMI) (Czech: Český hydrometeorologický ústav (ČHMÚ)) is within the Environmental Ministry of the Czech Republic. The head office and centralized workplaces of the CHMI, including the data processing, telecommunication and technical services, are located at the Institute's own campus in Prague. The CHMI has five major divisions:

Air Quality

Meteorology and Climatology

Hydrology

Finance and Administration

Information Technology

DISPERSION21

DISPERSION21 (also called DISPERSION 2.1) is a local scale atmospheric pollution dispersion model developed by the air quality research unit at Swedish Meteorological and Hydrological Institute (SMHI), located in Norrköping.The model is widely used in Sweden by local and regional environmental agencies, various industrial users, consultant services offered by SMHI and for educational purposes.

Finnish Meteorological Institute

The Finnish Meteorological Institute (Finnish: Ilmatieteen laitos, Swedish: Meteorologiska institutet, or simply FMI) is the government agency responsible for gathering and reporting weather data and forecasts in Finland. It is a part of the Ministry of Transport and Communications but it operates semi-autonomously.

The Institute is an impartial research and service organisation with expertise covering a wide range of atmospheric science activities other than gathering and reporting weather data and forecasts. The headquarters of the Institute is in Kumpula Campus, Helsinki, Finland.

ISC3

ISC3 (Industrial Source Complex) model is a popular steady-state Gaussian plume model which can be used to assess pollutant concentrations from a wide variety of sources associated with an industrial complex.

This model can account for the following:

Point, area, line, and volume sources

Settling and dry deposition of particles

Downwash

Separation of point sources

Limited terrain adjustmentISC3 operates in both long-term and short-term modes. The screening version of ISC3 is SCREEN3.

Very recently, the status of ISC3 as a Preferred/Recommended Model of the US Environmental Protection Agency has been withdrawn, but it can still be used as an alternative to the Preferred/Recommended models in regulatory applications with case-by-case justification to the reviewing authority.

Israel Meteorological Service

The Israel Meteorological Service (Hebrew: השירות המטאורולוגי הישראלי‎, HaSherut HaMete'orologi HaYisra'eli) is a unit of the Israeli Ministry of Transportation that is responsible for forecasting weather, meteorological data supply and climate research in Israel. Its origins begin in 1930's in a meteorological unit established by the British Mandate government mainly as a support to the evolving aviation needs at the time. After establishment of the state of Israel, it was incorporated into the newly established ministry of transport. It is a member of the World Meteorological Organization since 1949. the Israeli Meteorological Service runs more than 150 measuring stations across Israel. Located between Rishon LeZion, Mishmar HaShiva, and Holon, it is traditionally identified with also nearby Beit Dagan.

MERCURE

Mercure can also refer to the chain of hotels run by Accor. See Mercure Hotels.MERCURE is an atmospheric dispersion modeling CFD code developed by Électricité de France (EDF) and distributed by ARIA Technologies, a French company.MERCURE is a version of the CFD software ESTET, developed by EDF's Laboratoire National d'Hydraulique. Thus, it has directly benefited from the improvements developed for ESTET. When requested, ARIA integrates MERCURE as a module into the ARIA RISK software for use in industrial risk assessments.

NAME (dispersion model)

The NAME atmospheric pollution dispersion model was first developed by the UK's Met Office in 1986 after the nuclear accident at Chernobyl, which demonstrated the need for a method that could predict the spread and deposition of radioactive gases or material released into the atmosphere.

The acronym, NAME, originally stood for the Nuclear Accident ModEl. The Met Office has revised and upgraded the model over the years and it is now used as a general purpose dispersion model. The current version is known as the NAME III (Numerical Atmospheric dispersion Modeling Environment) model. NAME III is currently operational and it will probably completely replace the original NAME model sometimes in 2006.

National Atmospheric Release Advisory Center

The National Atmospheric Release Advisory Center (NARAC) is located at the University of California's Lawrence Livermore National Laboratory. It is a national support and resource center for planning, real-time assessment, emergency response, and detailed studies of incidents involving a wide variety of hazards, including nuclear, radiological, chemical, biological, and natural emissions.

NARAC provides tools and services to federal, state and local governments, that map the probable spread of hazardous material accidentally or intentionally released into the atmosphere.

NARAC provides atmospheric plume predictions in time for an emergency manager to decide if protective action is necessary to protect the health and safety of people in affected areas.

PUFF-PLUME

PUFF-PLUME is a model used to help predict how air pollution disperses in the atmosphere. It is a Gaussian atmospheric transport chemical/radionuclide dispersion model that includes wet and dry deposition, real-time input of meteorological observations and forecasts, dose estimates from inhalation and gamma shine (i.e., radiation), and puff or continuous plume dispersion modes. It was first developed by the Pacific Northwest National Laboratory (PNNL) in the 1970s.

It is the primary model for emergency response use for atmospheric releases at the Savannah River Site of the United States Department of Energy. It is one of a suite of codes for atmospheric releases and is used primarily for first-cut results in emergency situations. (Other codes containing more detailed mathematical and physical models are available for use when a short response time is not the over-riding consideration.)

RIMPUFF

RIMPUFF is a local-scale puff diffusion model developed by Risø DTU National Laboratory for Sustainable Energy, Denmark. It is an emergency response model to help emergency management organisations deal with chemical, nuclear, biological and radiological releases to the atmosphere.

RIMPUFF is in operational use in several European national emergency centres for preparedness and prediction of nuclear accidental releases (RODOS, EURANOS, ARGOS), chemical gas releases (ARGOS), and for airborne Foot-and Mouth Disease virus spread

Royal Netherlands Meteorological Institute

The Royal Netherlands Meteorological Institute (Dutch: Koninklijk Nederlands Meteorologisch Instituut or KNMI, pronounced [ˈkoːnɪŋklək ˈneːdərˌlɑnts ˌmeteoroˈloːɣis ˌɪnstiˈtyt]) is the Dutch national weather forecasting service, which has its headquarters in De Bilt, in the province of Utrecht, Netherlands.

The primary tasks of KNMI are weather forecasting, monitoring of climate changes and monitoring seismic activity. KNMI is also the national research and information centre for climate, climate change and seismology.

SAFE AIR

SAFE AIR (Simulation of Air pollution From Emissions Above Inhomogeneous Regions) is an advanced atmospheric pollution dispersion model for calculating concentrations of atmospheric pollutants emitted both continuously or intermittently from point, line, volume and area sources. It adopts an integrated Gaussian puff modeling system.

SAFE AIR consists of three main parts: the meteorological pre-processor WINDS (Wind-field Interpolation by Non Divergent Schemes) to calculate wind fields, the meteorological pre-processor ABLE (Acquisition of Boundary Layer parameters) to calculate atmospheric parameters and a lagrangian multisource model named P6 (Program Plotting Paths of Pollutant Puffs and Plumes) to calculate pollutant dispersion.

SAFE AIR is included in the online Model Documentation System (MDS) of the European Environment Agency (EEA) and of the .Italian Agency for the Protection of the Environment (APAT).

Swedish Meteorological and Hydrological Institute

The Swedish Meteorological and Hydrological Institute (Swedish: Sveriges meteorologiska och hydrologiska institut, abbreviated SMHI) is a Government agency in Sweden and operates under the Ministry of the Environment. SMHI has expertise within the areas of meteorology, hydrology and oceanography, and has extensive service and business operations within these areas.

Wind profile power law

The wind profile power law is a relationship between the wind speeds at one height, and those at another.

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