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Practical – Air Pollution Dispersion This practical has been designed to get you familiar with the Gaussian plume dispersion model. We discussed in the lectures how such models can be used to explain observed concentrations of air pollutants in an area and to test ‘what-if’ scenarios for pollution control and reduction. You will use the Gaussian Plume Model to calculate the ground-level concentration of various pollutants under differing conditions of atmospheric stability and source strength. You will initially do the exercises ‘by hand’ to get familiar with the procedures but the more usual method will be to use a web-based dispersion model to answer the remainder of the questions. By the end of this practical you should understand how meteorology and stack height dictate to a large extent, downwind air pollution levels on a local or regional scale. The Gaussian Plume Model.

The Gaussian Plume Model is the most frequently used atmospheric dispersion model. It is conceptually simple, well validated and easy to parameterise. It can be modified easily to account for different atmospheric stability and surface properties. In the following exercise we shall use forms of the basic equation which are most applicable to estimating ground-level concentration (glc) from a continuous point source of air pollution within about 100 km of the source and consistent with averaging times of 10-60 minutes. The spread of the plume is characterised by the standard deviations of the plume concentration in the y and z directions (σy and σz respectively). The spreading parameters (σy and σz ) are a function of downwind distance and can be found from Figure 1. They are also a function

of atmospheric stability which, for our purpose, can be given labels of A to F where A is an unstable atmosphere and F is very stable. These are known as the Pasquill Dispersion Classes and simple relationships between wind speed, daytime insolation and nocturnal cloud cover provide a simple parameterisation for stability. The relationship is found from Table 1.

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The equations to use: To predict glc directly downwind from the source

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To predict glc y metres off the x-axis

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where x = ground level concentration (g m-3) Q = source strength ( g s-1) σy, σz = plume standard deviations (m) H = effective height of emission (m) u = wind speed at height H (m s-1) Use the equations above to calculate glc under the following scenarios (remember to use Table 1 to estimate the atmospheric stability).

1. It is estimated that a burning dump emits 3 g s-1 of oxides of nitrogen. What is the ground-level concentration of NOx at a point 3 km directly downwind from the source on an overcast night with a wind speed of 7 m s-1? (Assume the dump is a point ground-level source with no effective rise)

2. It is estimated that 80 g s-1 of SO2 is being emitted from a petroleum refinery

from an average effective height of 60m. At 0800 on an overcast winter morning with the surface wind 6 m s-1, what is the glc directly downwind from the refinery at a distance of 500 m? (Assume wind speed at height H is 7 m s-1).

3. Under the conditions of problem 2, what is the concentration at the same

distance downwind but at a distance 50 m from the x-axis? 4. Repeat the calculations for problems 2 and 3 but assume that there is strong

daytime insolation with nearly calm wind speeds (let u = 1 m s-1). Record your answers in this Table. Problem Stability glc (µg m-3)

1 2 3

4a 4b -

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Dispersion Model on the Web Clearly, calculations such as those you have just done can now easily be programmed on a computer. I have written a gaussian plume dispersion model in the Java language and it can be run over the web. You will be able to access the model from the Env Poll web site eventually but for now use the following URL http://www.geos.ed.ac.uk/abs/research/micromet/java/plume.html. A screenshot shows what you should see when you load the web page.

The model is set up so that you can investigate the sensitivity of ground-level concentration (at various distances from an imaginary source in Leith Docks, Edinburgh) to changes in wind speed, source height and atmospheric stability. It is assumed in this model that the wind is blowing directly from the north. (There’s a bug in the contour routine at the present time of writing such that the plume centreline doesn’t coincide exactly with the contour value – I’m working on it!). Use the contours simply as a visual clue as to what happens as you change source height etc. The glc values recorded in the text box labelled ‘glc’ and attached to the mouse crosshair are the correct values to use. The default conditions for the dispersion model are: neutral stability, source height = 25m, emission rate = 100 g s-1, surface = grass. What you should do. 5. Complete the following table for glc estimated at 500m directly downwind from the source.

Assume default conditions otherwise.

Source emission strength (g s-1)

100 5 1000 10000

glc (g m-3)

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6. Using your knowledge of the gaussian plume equation, can you explain the results in the table in question 5?

7. Use the mouse and cursor to determine the position of the maximum glc under the following conditions (assume a stack height of 25m and a wind speed of 2 ms-1):

Neutral Stable unstable Distance downwind (m)

Distance crosswind (m)

What is your interpretation of these figures?

8. You should be able to move the mouse along or down one of the grid lines on the map and thus estimate glc down and across the plume (don’t worry about keeping exactly to the grid line). From such an exercise, sketch the plume shapes in the space below:

a) across the plume at a distance of 1000m downwind and b) directly along the plume i.e. 0 m crosswind

Sketch a Sketch b

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Note that if you use this simulation model to check your earlier hand calculations (questions 1-4 above) you will get different answers. This is to be expected since there will be differences in the specification of the spreading parameters σy and σz and rounding and graph-reading errors. You should be aware that predictions from such models are only accurate to ± 30% perhaps and even that is under optimum conditions in which the atmosphere and surface are specified accurately.

Table 1