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Air pollution caused by motor vehicles is harmful to public health. Managing the cause of this type of pollution is very difficult. Effective prediction and management of pollution can be attained only by computing air pollution. It is difficult to measure emissions directly, so it is estimated using a variety of models developed worldwide. The current study made an attempt to integrate the emission model COPERT with the traffic assignment model in CUBE software for predicting the traffic-related emissions of pollutants SO2, NO2 & PM2.5 in mixed traffic conditions by considering passenger car and light duty vehicles (LDVS), two-wheeler, auto and bus. The study also aimed to include fuel variables and meteorological variable humidity along with fleet composition, average speed and average monthly temperature as inputs. This would enable us to control the rising vehicular emission, by assessing current and future air quality and thereby implementing policy decisions.
Gopika Vinayakumar (Sun,) studied this question.