Computational intelligence estimation of natural background ozone level and its distribution for air quality modelling and emission control
- Publication Type:
- Conference Proceeding
- Citation:
- Proceedings of the 28th International Symposium on Automation and Robotics in Construction, ISARC 2011, 2011, pp. 1157 - 1163
- Issue Date:
- 2011-12-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 2010003837OK.pdf | 7.87 MB |
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Background ozone, known as the ozone that occurs in the troposphere as a result of biogenic emissions without photochemical influences, has a close relationship with human health risk. The prediction of the background ozone level by an air quality model could cover a wider region, whereas a measurement method can only record at monitoring sites. The problem is that simulation with deterministic models is quite tedious because of the nonlinear nature of some particular chemical reactions involved in the pollutant formulation. In this work, we present a reliable method for determination of the background ozone using the ambient measurement data. Our proposed definition can be used to determine the background level at any part of the globe and in any seasons without relying on data obtained at remote sites. A statistical model approach will be used for the estimation of the background ozone concentration, and a method for extrapolating the site data will be utilised to approximate the spatial distribution on the region. The proposed method will be applied in the Sydney basin to evaluate its effectiveness in background ozone determination. The results show the advantage of the proposed approach as a globally generic and computationally efficient way for the background ozone estimation with a reasonable accuracy.
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