International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

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M.Tech / M.E / PhD Thesis | Environmental Engineering | India | Volume 7 Issue 9, September 2018 | Rating: 7 / 10

Air Quality Prediction Modelling and its Validation in the Near Field of Urban Roadway of Delhi, India

Mantrana | Syed Kursheed Ahmad | Azhar Husain [2]

Abstract: Automobile exhaust is considerably important source of increasing carbon monoxide (CO) concentration in atmosphere and mainly in the urban cities. Considering the complex geometry of roadways, intersections and roundabout in urban centres of Delhi, that leads to increased emission of vehicular pollution mainly CO concentration. The main objective of the study is to monitor and predict the CO level concentration at micro-scale with an adequate methodology that permits to understand source-receptor relationship and to develop a proper strategies and planning to reduce concentration of CO pollutant. In urban centres of Delhi, with the help of CALINE-4 air pollution modelling software and digital air meter device used for average continuous CO monitoring for morning and evening peak hours, non-peak hours for 3 receptors location were done alongwith survey of peak traffic volume count for 14 hours on two weekdays and one weekend which includes peak hours and non-peak hours used for the prediction of concentration of CO level in air quality of road stretch of approx.3.2 Km of Gurjar Samrat Mihir Bhoj Marg, NH 24 of recently constructed Meerut Expressway starting from intersection near Indraprastha Park (or Sarai Kaley Khan Bridge) to Akshardham setu in Delhi. Predicted values shows increase in CO concentration with increase in timings with increase in number of vehicles. Traffic survey shows drastic change in the category of vehicles during non-peak hours mainly goods vehicles and heavy passengers vehicles. Monitoring results reflected increase in CO during non-peak hours expectedly due to presence of heavy vehicles and increase of background concentrations. The two different scenarios generated from the physical monitoring and from CALINE-4 software model has been compared. The prediction from the program has observed less values compared to the actual physical monitoring values, which shows the limitation of CALINE-4 software to an extent.

Keywords: Carbon Monoxide, CALINE-4, Prediction, Monitoring

Edition: Volume 7 Issue 9, September 2018,

Pages: 758 - 767

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