Urban roadside monitoring and prediction of CO, NO2 and SO2 dispersion from on-road vehicles in megacity Delhi. (July 2016)

• Record Type: Journal Article
• Authors: Mishra, Rajeev Kumar; Shukla, Ankita; Parida, Manoranjan; Pandey, Govind
• Is Part Of: Transportation research. Volume 46(2016)
• Page Start: 157
• Page End: 165
• Publication Date: 2016-07
• Subjects: Dispersion model -- Gaseous emission -- MS sheet; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2016.03.019
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: We measured gaseous pollutants at operational sites of metro and bus rapid transit system corridor. The GFLS model was developed in MS Excel worksheet system due to its user friendly properties. The concentration of gaseous pollutants was found higher during peak hour traffic flow condition. This model may be a reliable tool for the evaluation of urban air quality at roadside locations in Delhi. Abstract: The study inspects the traffic-induced gaseous emission dispersion characteristics from the urban roadside sites in Delhi, India. The concentration of pollutants viz. CO, NO2 and SO2 along with traffic and ambient atmospheric conditions at five selected local urban road sites were simultaneously measured. A developed General Finite Line Source Model (GFLSM) was used to predict the local roadside CO, NO2 and SO2 concentrations. A comparison of the observed and predicted values emission parameters using GFLS model has shown that the predicted values for SO2, CO and NO2 at all the selected local urban roadside locations are found to lie within the error bands of 5%, 6%, and 7% respectively. A high level of agreement was found between the monitored and estimated CO, NO2 and SO2 concentration data. From the study, it has also been established that the developed model exhibits the capability of reasonably predicting the characteristics of gaseous pollutants dispersion from on-road vehicles for the urban city air quality.