Abstract

 Vehicles are continuously emitting exhaust and evaporative gases that impacts urban environment. In a street canyon, the downwind concentrations result from the total contribution of background
 pollutant sources. For urban roads located close to high-rise buildings, maximum pollutant concentration can be found at about 20% of the canyon height, indicating entrapment of pollutants near the road surface. Normal horizontal and vertical dispersion and transport of pollutants occur as a results of inertial force, wind speed, and buoyant heat flux, provided there are no physical impediments like buildings near roads. In urban street canyons, pollutants become entrapped along the roadway.

Microscale pollutant dispersion models and field monitoring data from fixed stations at specific heights are often used to guide the development of emissions control strategies in the effort to attain National Ambient Air Quality Standards (NAAQS). Plus, those models are typically used to evaluate the environmental and sustainable development impacts of new construction projects. However models currently in use  often underestimate pollutant concentrations in micro-environments. Because air quality standards are set to protect public health, attention must be given to real-world exposure levels.

A theoretical formulation of a stochastic model has been developed to identify street canyon and vehicle wake effects on the transport  air pollution from urban road-micro-environments. It consists of wind distribution, emission dispersion, modified gaussian equation and stochastic prediction models. The formulation of the new model can better predict the pollutant levels for urban roads located near high-rise buildings. Model prediction results indicate that vehicle pollutant concentrations can become significantly elevated under worst case scenarios (at lower wind speeds). The model considers different fleet compositions (vehicle engine, dimensions, and fuel types), meteorological data, road-canyon geometry, and uninterrupted traffic flow characteristics for each section of urban road.

The influence of meteorology on the rate of dilution of background concentration on micro-environments has investigated based on the model. It is found that for wind speed from 1.5 to 3.5 m/sec around 40 to 80% of background concentration reduction occur from the road environment, in comparison to the level of pollutants at critical wind situa-tion (1m/sec). Particular pollu-tants namely, carbon monox-ide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and Nitrogen Oxides (NOx) are accounted for.

Another research has been performed and proposed  a future study to work and alleviate traffic pollution from urban roads, a logical approach to control urban traffic pollution, conveying intelligent traffic management. Congestion occur on an urban road due to the convergence of traffic flows from different streets. In such a  congested or polluted road, if pollution exceed Ambient Air Quality Standard levels or critical levels, a computer algorithm compiled within few logical statements and a number of control measurements in situ, in vitrio,  in the abstract, in real time, suggested to the city administration and or road commuters to alleviate traffic pollution on site by traffic planning and management; delivering congestion or pollution news via latest information technologies (radio waves, ITS technologies, electronic display and Internet Superhighway etc.), and reducing tolls in peak traffic hours. Possible real-time traffic simulation in Internet discussed to control traffic pollution.