CHETNA-Traffic: Street level CO2 and pollutant emission analysis from road traffic in Indian cities

India, a rapidly developing economy with the world’s largest population, has set an ambitious target of achieving net-zero carbon emissions by 2070. Road transport, contributing to 12% of India’s energy-related CO₂ emissions, plays a significant role in exacerbating urban air pollution. Given the country’s swift urbanization and the expansion of road transport to meet mobility demands, CO₂ emissions from this sector could potentially double by 2050, risking the achievement of long-term climate objectives. Our study presents a comprehensive analysis of traffic emissions across India, leveraging high-resolution mobility data at street level, including vehicle count, types, and speeds for 100 different Indian cities. We use statistical and machine learning methods to improve data quality and extrapolate mobility data to all city traffic using city-level vehicle registration data. Here, we focus on understanding traffic and congestion patterns within and between cities, using additional data on population, urban structure, road network, public transport supply, and socio-economic variables. Finally, we simulate hourly CO₂ and pollutant emissions at a street level using the COPERT model, which includes speed and vehicle-type dependent emission factors. With this study, we also aim to explore scenarios for reducing pollution, a critical issue for Indian metropolises. The findings from this study will provide valuable insights into the environmental impact of road traffic in India and inform strategies for pollution reduction. This work is part of the CHETNA project (City-wise High-resolution carbon Emissions Tracking and Nationwide Analysis), which leverages artificial intelligence and advanced datasets to deliver high-resolution, near real-time daily CO₂ and air pollutant emissions data for over 100 Indian cities.