Tesfa, Belachew, Gu, Fengshou, Anyakwo, Arthur, Al Thobiani, Faisal and Ball, Andrew (2012) Prediction of metal pm emission in rail tracks for condition monitoring application. In: Railway Condition Monitoring and Non-Destructive Testing (RCM 2011), 5th IET Conference on. IET, London, pp. 1-6.
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Exposure to particulate material (PM) is a major health concern in megacities across the world which use trains as a primary public transport. PM emissions caused by railway traffic have hardly been investigated in the past, due to their obviously minor influence on the atmospheric air quality compared to automotive transport. However, the electrical train releases particles mainly originate from wear of rails track, brakes, wheels and carbon contact stripe which are the main causes of cardio-pulmonary and lung cancer. In previous reports most of the researchers have focused on case studies based PM emission investigation. However, the PM emission measured in this way doesn’t show separately the metal PM emission to the environment. In this study a generic PM emission model is developed using rail wheel-track wear model to quantify and characterise the metal emissions. The modelling has based on Archard’s wear model. The prediction models estimated the passenger train of one set emits 6.6mg/km-train at 60m/s speed. The effects of train speed on the PM emission has been also investigated and resulted in when the train speed increase the metal PM emission decrease. Using the model the metal PM emission has been studied for the train line between Leeds and Manchester to show potential emissions produced each day. This PM emission characteristics can be used to monitor the brakes, the wheels and the rail tracks conditions in future.
|Item Type:||Book Chapter|
|Additional Information:||© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
|Uncontrolled Keywords:||Railways, Metal particle emission, Emission prediction, Wear models|
|Subjects:||T Technology > TF Railroad engineering and operation|
|Schools:||School of Computing and Engineering
School of Computing and Engineering > Diagnostic Engineering Research Centre
|Depositing User:||Graham Stone|
|Date Deposited:||10 Aug 2012 13:07|
|Last Modified:||06 Dec 2016 05:47|
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