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• W4296190956 abstract "Vehicular emissions are the major source of air quality deterioration in Indian megacities. However, there is uncertainty in vehicular emission estimation due to the paucity of vehicular use and travel characteristics, and there is no specific methodology to assess the same. Thus, this study presents a methodology to capture the urban in-use vehicular characteristics. Additionally, it evaluates current vehicular emissions in Mumbai and estimates future emission levels for the year 2030, taking into account various policy interventions. Data for the study were collected via questionnaire surveys at fuel stations across Greater Mumbai – a first in western India. Exhaust and non-exhaust vehicular emissions were developed using the “bottom-up” methodology. Six scenarios were tested for exhaust vehicular emissions and energy consumption under various policy interventions. Monte-Carlo Simulations (MCS) were carried out to find the uncertainties in the vehicular emission estimation. Results showed that approximately 66% of the registered vehicles ply on Mumbai roads, and the on-road fuel efficiency is 12–33% less than the reported lab-based studies. Our study findings suggest that conducting surveys at three fuel stations is adequate for determining urban in-use vehicular characteristics with <5% bias. Reduction in vehicular emissions calls for stringent norms for private passenger vehicles and regulation of non-exhaust vehicular emissions. Given projected vehicular emissions for 2030, urban cities like Mumbai will have to inevitably replace conventional vehicles with electric vehicles to achieve the Paris agreement, which is to limit global warming well below 2 °C." @default.
• W4296190956 created "2022-09-18" @default.
• W4296190956 creator A5003060638 @default.
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• W4296190956 date "2022-11-01" @default.
• W4296190956 modified "2023-10-02" @default.
• W4296190956 title "Assessing Mumbai's in-use vehicular characteristics, current emissions, and future projections under various policy interventions" @default.
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• W4296190956 doi "https://doi.org/10.1016/j.jclepro.2022.134145" @default.
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