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    Measurement and modelling of nitrogen dioxide (NO2) emissions: a marker for traffic-related air pollution in Doha, Qatar

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    Date
    2015-07-20
    Author
    Al-Naimi, Noora
    Balakrishnan, Perumal
    Goktepe, Ipek
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    Abstract
    In the State of Qatar, recent statistics show a continued increase in the motor-vehicle fleet commensurate with population growth and economic development. This trend, together with the rapid expansion of urban areas and the increased dependence on automobiles, has resulted in an increase in pollution near traffic sources, indicating that the risk of exposure to vehicles’ emissions is higher and that these emissions must be considered in terms of their spatial and temporal occurrence. So far, there are no studies conducted in Qatar to evaluate the traffic-related air pollution. This study is carried out to monitor the levels of nitrogen dioxide (NO2) as a marker of pollution related to traffic. The aim of this study is to build a baseline for traffic-related pollution in Qatar by monitoring and modelling NO2 emissions. The levels of traffic-related air pollution by NO2 were investigated at six major intersections along the C-ring road. The relationship of NO2 was established with traffic volume in each intersection during December 2012 and March–April 2013. Significant differences were established between the pollutant concentrations in each intersection. The CALifornia LINE Source Dispersion Model, version 4 air dispersion model employed had estimated the influence of the measured NO2 concentration on the predicted NO2 values by 31.12%. The low percentage may have accounted for the uncertainties brought by the vehicle emission factor and non-availability of temporal dynamics during the time of sampling. Non-parametric Spearman’s correlation test resulted in a significant correlation between measured and predicted values of NO2 concentrations, rs = 0.525 and p = 0.012.
    DOI/handle
    http://dx.doi.org/10.1080/19475683.2015.1057225
    http://hdl.handle.net/10576/5481
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    • Biological & Environmental Sciences [‎931‎ items ]
    • Earth Science Cluster [‎216‎ items ]

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