USING POLAR COORDINATE SYSTEM TO UNDERSTAND EMISSION SOURCES (2)

USING POLAR COORDINATE SYSTEM TO UNDERSTAND EMISSION SOURCES

Compiled by: Mandilakhe MsutuGraduate Intern: Air Quality Monitoring

Laboratory

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Outline…

• What are Polar Coordinates?• Reason for their development?• How can they be used in Air Quality Monitoring?• Advantages• Limitations• Conclusion• References• Acknowledgements

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What are Polar Coordinates?

• A pair of coordinates locating the position of a point in a plane, the first being the length of the straight line ( r ) connecting the point to the origin, and the second the angle ( θ ) made by this line with a fixed line (Polar Axis)

• Different from coordinate system which uses x and y coordinates to locate every point on plane

• One point in a plane has one pair of coordinates but it has many polar coordinates

• P(r, 0 ≤

Reasons for their development?

• Traditional Methods:- cannot be computed Low scalability Do not work well with Large and complex data Cannot produce high-level correlation data (scatter-plots) 2-dimentional data • 3-D bivariate polar plots were developed

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How can they be used in AQM?

• Represent concentration of a pollutant as a function of distance

• Wind speed and wind direction as well as the concentration are used

• Wind Speed=Distance• Wind Direction= Angle• Concentration= Colour• Wind speed and direction are

highly effective at discriminating different emission sources

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Data Used for Polar Plots

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Three Cases

• Case 1: High wind speed= Low concentration

• Case 2: Low wind speed= High concentration

• Care 3: High wind speed= High concentration….the source is at a height or the major emission source is in the direction of the wind.

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Polar Plots on ARM

• Open ARM→ Reports → Wind→ Station→ Pollutant→ Time period→ WindPolar and select wind speed and direction.

Windpolar: Tableview SO2 04/2015

Wind-Polar for Tableview

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Relationship between Wind-polar and Wind-rose

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The source plays a major role

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Imagine

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North-West

• Not enclosed• Visible smoke- air pollution• Gas emissions (SO2, benzene)

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North-East

• No visible smoke• Less air pollution• Tanks covered

Advantages

• Produce high correlated data Example: Users may observe that the amount of S02 is high at a certain wind speed, they may go further to identify the direction, the temperature, the amount of C02 and NOx etc• Allows users to query by wind speed and direction• Reduce conflict• Saves time• Cheaper

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Limitations

• Subjected to uncertainty• Can be wrong due to un-calibrated instruments• Some of our sites do not have MET equipment

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Conclusion

• Helps to easily identify the emission sources• Produce high correlated data• Reduce conflict• Saves time

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References

• Carslaw, D. C., Beevers, S. D., Ropkins, K., Bell, M. C., 2006. Detecting and quantifying aircraft and other on-airport contributions to ambient nitrogen oxides in the vicinity of a large international airport. Atmospheric Environment 40 (28), 5424–5434.

• Huamin. Q, Chan. W, Xu.A & Chung. K (2007). IEEE Transactions on Visualization and Computer Graphics, vol. 13, no.6, pp. 1408-1415, Nov-Dec. 2007

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Acknowledgements

• Mr. S. Mackenzie- “The amount of experience you gain in scientific services is entirely up to you”• Dr. R. Magoba• AQM Team

Thank You

For queries contact Mandilakhe.Msutu@capetown.gov.za