PREDICTION OF PM2.5 FROM VEHICULAR POLLUTION BY USING CALINE4 AT HYDERABAD

Abstract

This paper presents a study regarding the vehicular pollution by using CALINE4. All over the world concern is growing over the health effects of emissions from internal combustion engines in the transport fleet. Studies conducted using air pollution exposure information and various health indicators, such as hospital admissions, are invariably showing up real and dramatic effects. It is broadly demonstrated that air pollution in urban areas is mainly due to the intense use of motorized transport for travelling, with particular regard to private cars and heavy goods vehicles. This is a top priority issue for transportation planners and public authorities, given the harmful effects of pollution to human health and the environment An efficient and effective approach for the prediction of air pollution due to road transport is necessary to improve ambient air quality. Highway dispersion models are widely used for prediction of air quality along road and highway corridors. Various input parameters used by these models for prediction of air quality along the road corridors. In the present study, Prediction of pollutants PM2.5 by CALINE4 model was carried out
under mixed traffic conditions. The road corridor selected at Sanath nagar, Hyderabad (India) was a stretch which connects National Highway-65 (NH-65) to Fathe Nagar in the city. The selected corridor caters to both inter-city and intra-city traffic and had mixed traffic conditions. Prediction by CALINE4 model was carried out for 24 hours average input datasets representing different meteorological (wind speed, wind direction, mixing height, stability class), traffic (traffic volume and emission factors) and road characteristic (roadway width) along with terrain (surface roughness) characteristic.