Optimizing strategies for air pollution mitigation in India: Modelling energy-technology-emission scenarios and impacts



Air pollution or exposure to high concentrations of fine particulate matter (PM-2.5, particles with aerodynamic diameter less than 2.5 um), causes death, disease and shortens life expectancy. The Indian National Clean Air Programme (NCAP) proposes an ambitious goal of significant reduction in ambient PM2.5 concentrations by 2024 and into the future. Over the past decade, the development of a new generation of reduced-complexity air quality models (RCMs) such as InMAP (Intervention Model for Air Pollution [1]) has enabled even non-specialists to run hundreds or thousands of air pollution mitigation simulations on desktop computers. In this project, the student would participate in the development of an India specific version of InMAP (SMoG-InMAP-India), with US university partners, based on our SMoG-India emission inventory (https://ncapcoalesce.iitb.ac.in/resources/smog-india-emission-inventory/).

Reduction in ambient PM2.5 concentrations can be achieved through different sector specific technological combinations. The student will work on selected sectors such as transport, residential, and agriculture and develop scenarios for adoption of air pollution mitigation technologies. The scenario development will be based on technology cost, TRL level, and other factors [2].

These scenarios will be used to perform InMAP simulations to develop and assess multi-sector, multi-scale air pollution mitigation strategies for India. Optimized strategies would be developed from sector specific interventions and their combinations. Overall, the project will involve reduced-complexity model (RCM) development, model validation, and air pollution policy analysis.

Pre-requisite: The candidate should be comfortable with modelling and simulation and be willing to develop strong skills in programming in python and MATLAB.

Related literature

  1. Tessum CW, Hill JD, Marshall JD (2017) InMAP: A model for air pollution interventions. PLoS ONE 12(4): e0176131. https://doi.org/10.1371/journal.pone.0176131
  2. Saraf, N., Shastri, Y. System dynamics-based assessment of novel transport options adoption in India. Clean Techn Environ Policy (2022). https://doi.org/10.1007/s10098-022-02398-8