Fuel losses and assessment of air quality at selected traffic intersections in Delhi.

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Bibliographic Details
Title:	Fuel losses and assessment of air quality at selected traffic intersections in Delhi.
Authors:	Sharma, Niraj¹, Advani, Mukti¹ mukti7@gmail.com, Dhyani, Rajni¹
Source:	Current Science (00113891). 1/25/2026, Vol. 130 Issue 2, p136-147. 12p.
Subjects:	Air quality, Road interchanges & intersections, Capital cities, Motor vehicle driving, Energy consumption, Air pollutants, Transportation industry
Geographic Terms:	New Delhi (India)
Abstract:	The rapid growth in the road transport sector has resulted in high consumption of fossil fuels and increased air pollution levels in urban areas, often exceeding the prescribed air quality standards set by various regulatory agencies. The direct effect of vehicle idling is fuel loss, along with related emissions that contribute to heightened air pollution levels. The CAL3QHC model, a Gaussian-based air quality dispersion model approved by the United States Environmental Protection Agency, is specifically developed for predicting air quality at traffic intersections. This model is capable of predicting pollutant concentrations generated from long queues of vehicles waiting at signals (idling condition). The present study focuses on the performance evaluation of the CAL3QHC model in Delhi by utilising local traffic, meteorological, and morphological data. The methodology adopted for estimating signalised intersections, including queue parameters such as signal timing, red signal duration, approach traffic volume, and saturation flow rate, is also discussed. The CAL3QHC model has been employed to predict CO and PM2.5 concentrations at three selected signalised traffic intersections. Simultaneously, 48 h traffic volume counts were conducted at these intersections on weekends (Sunday) and weekdays (Monday) during both summer and winter seasons. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	The rapid growth in the road transport sector has resulted in high consumption of fossil fuels and increased air pollution levels in urban areas, often exceeding the prescribed air quality standards set by various regulatory agencies. The direct effect of vehicle idling is fuel loss, along with related emissions that contribute to heightened air pollution levels. The CAL3QHC model, a Gaussian-based air quality dispersion model approved by the United States Environmental Protection Agency, is specifically developed for predicting air quality at traffic intersections. This model is capable of predicting pollutant concentrations generated from long queues of vehicles waiting at signals (idling condition). The present study focuses on the performance evaluation of the CAL3QHC model in Delhi by utilising local traffic, meteorological, and morphological data. The methodology adopted for estimating signalised intersections, including queue parameters such as signal timing, red signal duration, approach traffic volume, and saturation flow rate, is also discussed. The CAL3QHC model has been employed to predict CO and PM2.5 concentrations at three selected signalised traffic intersections. Simultaneously, 48 h traffic volume counts were conducted at these intersections on weekends (Sunday) and weekdays (Monday) during both summer and winter seasons. [ABSTRACT FROM AUTHOR]
ISSN:	00113891
DOI:	10.18520/cs/v130/i2/136-147