| Author: | Mak, Kai-long |
| Title: | Developing a tunnel based model for monitoring vehicle emissions |
| Degree: | M.Phil. |
| Year: | 2008 |
| Subject: | Hong Kong Polytechnic University -- Dissertations. Automobiles -- Motors -- Exhaust gas -- Simulation methods. |
| Department: | Department of Civil and Structural Engineering |
| Pages: | xiv, 143 leaves : ill. ; 30 cm. |
| Language: | English |
| Abstract: | Tunnel emission models are one of the most useful tools in measuring and quantifying vehicular emissions. A speed modified simple mass balance model has been developed for the purposes of monitoring the change of pollutant emissions. This research intends to develop a new effective emission monitoring model on existing tunnel monitoring data. The result will be useful for the government to assess the effectiveness of her air pollution abatement programmes. The methodology involves collecting speed profiles, pollutant concentration profiles, analyzing the data statistically, and developing a speed modified simple mass balance model. Instantaneous vehicular exhaust concentration data was collected by using an instrumented car travelling through tunnel. The traffic flow-speed curve for tunnel was developed successfully. A strong correlation between vehicle speed and pollutant concentration was obtained in the field work. The impact of speed was then introduced to modify the simple mass balance model to estimate pollutant emission factors based on this tunnel study. In the validation test, the speed modify simple mass balance model was compared with the emission factor obtained by remote sensing technique. By statistical analysis, there was no significant difference between the speed modified emission factor and remote sensing estimation. Compared to the popular pollutant emission factor models, it appear that the refined speed modify mass balance model is robust in developing tunnel based emission factor model. |
| Rights: | All rights reserved |
| Access: | open access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b22396755.pdf | For All Users | 3.39 MB | Adobe PDF | View/Open |
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