The transportation sector is one of the major air pollution sources in cities and accounts for about 72% of total air pollution in Tabriz, Iran. The economic burden of air pollution on Iran’s economy was estimated to be 8 and 10 billion dollars in 2005 and 2010, respectively. Using air pollution models, including emission and dispersion models, has been proposed as a logical solution to overcome problems such as expensive measurement methods and in some cases, difficulty and impossibility of direct measurements. In this paper, IVE emission model was used for estimating emission amounts and emission factors of taxi fleet of Imam Khomeini Street, one of main and busiest streets in Tabriz, as a representative street and for studying effects of different scenarios. AERMOD dispersion model was used for investigating the dispersion pattern of emitted pollutants from this fleet and to estimate the effect of using local base emission factors and replacement of present taxi fleet by environmental friendly vehicles in this city. CO, CH4, and NOx pollutants with quantities of 108, 20.7, and 5.4 g/km have the highest emission factor among all pollutants. Amount of hourly emissions per each pollutant, daily emission amount by technology types, and daily emission amount of each technology by pollutant types were also examined. CO emission has the highest amount at 7–8 in the morning, and at noon hours, emission of NOx and VOC increases. Technologies with old fuel injection and emission control systems and higher mileage have higher level of pollution emission. Investigating dispersion of pollutants from this fleet in the atmosphere shows pollutants movement in the northwest direction. Performance statistics of AERMOD model, such as FB, NMSE, MG, VG, FAC2, and R by use of pollution level of two adjacent air pollution monitoring stations were determined to continue. Three air pollution scenarios are used to assay effects of using site-specific base emission factors; replacement of worn-out portion of fleet with two distinct technology types (gasoline fuel and CNG fuel) were investigated. As a result under the first and second scenarios, 6.4% and 3.9% decrease of GWP would be estimated respectively and under the third scenario, 7.8% increase of GWP relative to the present study was observed.
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