Published May 18, 2024 | Version v1
Dataset Open

Vehicle Stock Numbers and Survival Functions for On-road Exhaust Emissions Analysis in India: 1993-2018

Description

Final publication on the vehicle stock numbers under review (2024 May).

Preprint is available here
Guttikunda, S. K. Vehicle Stock Numbers and Survival Functions for On-road Exhaust Emissions Analysis in India: 1993-2018. Preprints 2024, 2024051393. https://doi.org/10.20944/preprints202405.1393.v1

Older publication:
Re-fueling road transport for better air quality in India
https://www.sciencedirect.com/science/article/abs/pii/S0301421514000020

An informed emissions inventory can help define the baseline, use that baseline to formulate an effective air quality management plan and track progress or lack thereof, and use the results for research, innovation, and public awareness. In air quality management, at urban and regional levels, road transport remains the cornerstone of residential, commercial, and industrial activities, and the vehicle exhaust emissions maintain the position of one of the key contributing sources.

In Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads, contribute to as much as 50% of particulate matter pollution in a year. So, having access to a vehicle exhaust emissions inventory that is reliable and replicable is critical for air quality management and one of the key inputs to this exercise is vehicle stock numbers. These numbers are typically obtained from vehicle registration databases, traffic surveys, and other governmental records, and often require time consuming data cleaning protocols before they can used for emissions analysis.

This database provides a clean and open-access vehicle stock database, as registered and in-use fleet, for the period covering 1993 and 2018, for all India and states, along with an estimate of age-mix of the vehicles using survival functions.

VAPIS Excel players included here are

  • ·A method to convert fleet average speeds and fleet average travel time per day into vehicle km travelled per day.
  • ·A method to calculate how many additional buses are required to support odd-even or an equivalent scheme (with and without fuel mix exemptions).
  • ·A method to calculate total fuel wasted from idling in the city and to calculate savings from traffic management.
  • ·A method to calculate fuel and emission benefits of shifting a share of 2-wheeler and 4-wheeler trips to buses and non-motorized transport.
  • ·A method to estimate vehicle exhaust emission factors using emission standards and deterioration rates.
  • ·An example set of survival rates based on vehicle age for nine broad vehicle categories to convert registered number of vehicles to in-use number of vehicles.
  • ·A method to spatially disaggregate (grid) the total vehicle exhaust emissions using multiple grid-level proxies as weights such as density (km per grid) of various road types, population density, landuse-landcover, and information on commercial and industrial activities.
  • ·A library of emission factors for aerosols and gaseous species.

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