India has some of the most polluted cities in the world. Rising air pollution is taking a heavy toll on the health and productivity of citizens. With recent studies pegging the death toll due to air pollution at 9 million, we need urgent, effective solutions.
At CSTEP, we are working with state pollution control agencies and the Central Pollution Control Board to scientifically identify the sources of pollution for effective and targeted interventions. With the use of emerging technologies such as low-cost sensors, mobile monitoring, and satellite-based monitoring of air pollution, CSTEP is looking at ways to make data on air pollution comprehensive, robust, and accessible.
The capacity-building measures initiated by CSTEP ensure that state agencies can scientifically assess, interpret, and formulate effective strategies to check rising air pollution.
On the National Clean Air Programme
When the Indian government launched the National Clean Air Programme (NCAP) in 2019, it was to cut the concentration of atmospheric Particulate Matter (PM) by 20-30% by 2024, from 2017 levels. This was later revised to 40% by 2026.
ICAS 2024: The Participatory Future of Air Quality Management
The Center for Study of Science, Technology and Policy (CSTEP) announces its flagship event on air pollution India Clean Air Summit (ICAS) 2024. The event is organised by the Air Quality sector at CSTEP to provide a platform for driving collaborative action on air quality in India.
India’s need to curb black carbon emissions
At the COP26 climate talks in Glasgow in November 2021, India pledged to achieve net-zero emissions by 2070, positioning itself as a frontrunner in the race to carbon neutrality. According to the Ministry of New and Renewable Energy, India had installed a renewable energy capacity of over 180 GW by 2023 and is expected to meet its target of 500 GW by 2030.
Multi-season mobile monitoring campaign of on-road air pollution in Bengaluru, India
Mobile monitoring can supplement regulatory measurements, particularly in low-income countries where stationary monitoring is sparse. Here, we report results from a ~ year-long mobile monitoring campaign of on-road concentrations of black carbon (BC), ultrafine particles (UFP), and carbon dioxide (CO2) in Bengaluru, India. The study route included 150 unique kms (average: ~22 repeat measurements per monitored road segment).
Urban air-quality estimation using visual cues and a deep convolutional neural network in Bengaluru (Bangalore), India
Mobile monitoring provides robust measurements of air pollution. However, resource constraints often limit the number of measurements so that assessments cannot be obtained in all locations of interest. In response, surrogate measurement methodologies, such as videos and images, have been suggested. Previous studies of air pollution and images have used static images (e.g., satellite images or Google Street View images).