The clean air action plans developed by non-attainment cities under National Clean Air Program (NCAP) propose various air pollution mitigation strategies. But given the size of the air quality challenge, it is imperative that funds for such these strategies are used strategically and judiciously.
Learnings from the EASIUR model – Estimating Air Pollution Social Impact Using Regression—developed by the Carnegie Mellon University are helping to show the way forward. EASIUR helps to quantify the social costs of air pollution, information that is crucial to inform the development of policy solutions for cleaner air, better public health and climate action.
Shakti is enabling the customization of the EASIUR Model to the Indian context so that Indian cities can use it to prioritise and assess the cost effectiveness of air pollution management strategies. The model will help track per tonne impact metrics of PM2.5 and its precursors along with source receptor matrices. Through these results, cities will be able to map changes in PM2.5 concentrations and locate specific populations that will be impacted.