S
Sharad Gokhale
Researcher at Indian Institute of Technology Guwahati
Publications - 51
Citations - 1305
Sharad Gokhale is an academic researcher from Indian Institute of Technology Guwahati. The author has contributed to research in topics: Air quality index & Traffic flow. The author has an hindex of 17, co-authored 42 publications receiving 1043 citations. Previous affiliations of Sharad Gokhale include Indian Institute of Technology Delhi & Indian Institutes of Technology.
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Evaluating effects of traffic and vehicle characteristics on vehicular emissions near traffic intersections
TL;DR: In this paper, the authors examine the effect of traffic, vehicle and road characteristics on vehicular emissions with a view to understand a link between emissions and the most likely influencing and measurable characteristics.
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Urban real-world driving traffic emissions during interruption and congestion
Arti Choudhary,Sharad Gokhale +1 more
TL;DR: In this paper, the authors measured emissions from passenger cars and auto-rickshaws during peak and off-peak hours and analyzed according to different mileages with the instantaneous speed and acceleration for interrupted and congested traffic conditions.
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Passive control potentials of trees and on-street parked cars in reduction of air pollution exposure in urban street canyons.
K.V. Abhijith,Sharad Gokhale +1 more
TL;DR: This study investigates the passive-control-potentials of trees and on-street parked cars on pedestrian exposure to air pollutants in a street canyon using three-dimensional CFD and found tree crown with high porosity and low-stand density in combination with parallel or perpendicular car parking reduced the pedestrian exposure considerably.
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A Review of Deterministic, Stochastic and Hybrid Vehicular Exhaust Emission Models
Sharad Gokhale,Mukesh Khare +1 more
TL;DR: In this article, the authors present a review of deterministic and stochastic based vehicular exhaust emission models that may be hybridized and thus generate a hybrid model with improved prediction accuracy.
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Performance evaluation of air quality models for predicting PM10 and PM2.5 concentrations at urban traffic intersection during winter period.
Sharad Gokhale,Namita Raokhande +1 more
TL;DR: The study has shown that the CAL3QHC model would make better predictions compared to other models for varied meteorology and traffic conditions and has outperformed for both particulate sizes and for all the wind classes, which therefore can be optional for air quality assessment at urban traffic intersections.