Estimating emissions from the Indian transport sector with on-road fleet composition and traffic volume

Urbanization and rising household incomes in India have led to growing transport demand, particularly during 1990-2010. Emissions from transportation have been implicated in air quality and climate effects. In this work, emissions of particulate matter (PM2.5 or mass concentration of particles smaller than 2.5 um diameter), black carbon (BC) and organic carbon (OC), were estimated from the transport sector in India, using detailed technology divisions and regionally measured emission factors. Modes of transport addressed in this work include road transport, railways, shipping and aviation, but exclude off-road equipment like diesel machinery and tractors. For road transport, a vehicle fleet model was used, with parameters derived from vehicle sales, registration data, and surveyed age-profile. The fraction of extremely high emitting vehicles, or superemitters, which is highly uncertain, was assumed as 20%. Annual vehicle utilization estimates were based on regional surveys and user population. For railways, shipping and aviation, a top-down approach was applied, using nationally reported fuel consumption. Fuel use and emissions from on-road vehicles were disaggregated at the state level, with separate estimates for 30 cities in India. The on-road fleet was dominated by two-wheelers, followed by four-and three-wheelers, with new vehicles comprising the majority of the fleet for each vehicle type. A total of 276 (-156, 270) Gg/y PM2.5, 144 (-99, 207) Gg/y BC, and 95 (-64, 130) Gg/y OC emissions were estimated, with over 97% contribution from on-road transport. Largest emitters were identified as heavy duty diesel vehicles for PM2.5 and BC, but two-stroke vehicles and superemitters for OC. Old vehicles (pre-2005) contributed significantly more (similar to 70%) emissions, while their share in the vehicle fleet was smaller (similar to 45%). Emission estimates were sensitive to assumed superemitter fraction. Improvement of emission estimates requires on-road emission factor measurements for all vehicle types and a better understanding of vehicle utilization and superemitter fraction. (C) 2014 Elsevier Ltd. All rights reserved.