science

NAME (dispersion model)

NAME (dispersion model) is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand NAME (dispersion model) rather than just read about it. In short: 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.

Key takeaways

NAME (dispersion model) belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect NAME (dispersion model) to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of NAME (dispersion model) from memory before moving on to harder problems.

Reference excerpt

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 Modelling Environment) model. NAME III is currently operational and it will probably completely replace the original NAME model sometimes in 2006.

Features and capabilities of NAME NAME (in its current NAME III version) is a Lagrangian air pollution dispersion model for short range to global range scales. It employs 3-dimensional meteorological data provided by the Met Office's Unified National Weather Prediction Model. Random walk techniques using empirical turbulence profiles are utilized to represent turbulent mixing. In essence, NAME follows the 3-dimensional trajectories of parcels of the pollution plume and computes pollutant concentrations by Monte Carlo methods — that is, by direct simulation rather than solving equations. NAME uses a puff technique when modelling dispersion over a short range which shortens the time needed to compute the pollutant concentrations at the receptors. The model has the capability to calculate: the rise of buoyant plumes; deposition of pollution plume components due to rainfall (i.e., wet deposition); dry deposition; plume chemistry focusing on sulphate and nitrate chemistry; plume depletion via the decay of radioactive materials; the downwash effects of buildings. The model can also be run 'backwards' to generate maps that locate possible plume originating sources.

The Met Office's commitments to emergency response service The Met Office has international commitments to provide emergency response dispersion modelling services for releases of hazardous gases and materials into the atmosphere. Such events include the release of radioactive materials and emissions from erupting volcanoes. Those commitments are met by an operational group known as EMARC who are supported by a Met Office team of dispersion modelling staff. That team is also responsible for the scientific development of NAME III which, combined with the Met Office numerical weather prediction model, is used to provide the dispersion modelling services needed to implement the listed commitments:

The WMO (World Meteorological Office) has designated the Met Office to operate one of the worldwide RSMCs (Regional Specialist Meteorological Centre) The Met Office has also been designated a VAAC (Volcanic Ash Advisory Centre) which is part of the IAVW (International Airways Volcano Watch) set up by the ICAO (International Civil Aviation Organization). Over the years, NAME has been applied to radioactive releases, the Kuwaiti oil fires, major industrial fires and chemical spills, and two volcanic eruptions in Iceland.

See also Bibliography of atmospheric dispersion modeling Atmospheric dispersion modeling List of atmospheric dispersion models UK Dispersion Modelling Bureau

References

Further reading For those who are unfamiliar with air pollution dispersion modelling and would like to learn more about the subject, it is suggested that either one of the following books be read:

Turner, D.B. (1994). Workbook of atmospheric dispersion estimates: an introduction to dispersion modeling (2nd ed.). CRC Press. ISBN 978-1-56670-023-8. www.crcpress.com Beychok, M.R. (2005). Fundamentals Of Stack Gas Dispersion (4th ed.). self-published. ISBN 978-0-9644588-0-2. www.air-dispersion.com

External Links "Met Office Dispersion Model". Met Office. Retrieved 15 December 2018. "NAME Documentation". Met Office. Retrieved 29 July 2026.

Worked examples

Example 1 — a first encounter with NAME (dispersion model)

Start with the simplest possible case. Write down what NAME (dispersion model) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to NAME (dispersion model) before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about NAME (dispersion model) ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of NAME (dispersion model)

In research: NAME (dispersion model) appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses NAME (dispersion model) in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: NAME (dispersion model) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Atmospheric dispersion modeling, Met Office, so understanding it makes those chapters shorter.
In everyday life: Look for NAME (dispersion model) outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study NAME (dispersion model) in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what NAME (dispersion model) means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain NAME (dispersion model) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is NAME (dispersion model) in simple terms?

Why does NAME (dispersion model) matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study NAME (dispersion model)?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on NAME (dispersion model).