The Atmospheric Composition Modelling group focuses on enhancing the current understanding of atmospheric composition and its evolution. We synthesise weather prediction, dispersion, chemistry transport, and reduced complexity models, which can be employed to comprehend the intricate atmospheric processes influencing air quality over a region. The group utilises a variety of ground- and space-based atmospheric measurements to validate model outcomes. By harmonising diverse models and observations, we aim to provide insights for formulating effective air pollution control strategies within a specified geographical area.
Analyst/Senior Analyst
For this post, we are seeking candidates with a background in atmospheric sciences, air pollution, etc., with proficiency in FORTRAN, shell scripting, and python on high-performance computing platforms based on Unix/Linux. The applicant should have experience of working with satellite datasets (e.g., MODIS, TROPOMI, etc.) and surface measurements such as CPCB CAAQMS/NAMP and sensor data. She/he should be able to perform data analysis and visualisation with a strong understanding of statistical methods.
Senior Associate
For this post, we are seeking candidates with expertise in weather/chemistry transport modelling, and satellite data analysis and visualisation. The applicant must have experience of working with Weather Research and Forecasting model with Chemistry (WRF-Chem) and/or Comprehensive Air Quality Model with Extensions (CAMx) on High-Performance Computing (HPC) platforms.
Introducing the CSTEP Air Quality sector
Air quality can be improved through well-designed air quality management plans that are effectively implemented. For this, we need to know the sources impacting a certain location; the emissions contributed by each source; the interventions that can reduce these emissions; the cost of those interventions; and once implemented, their effectiveness. The sources in question can be local (e.g., city traffic emissions), transboundary (e.g., an industry outside a city or sources in another state), or natural (e.g., desert dust or wildfires).
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.
Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural India
Lower-cost air pollution sensors can fill critical air quality data gaps in India, which experiences very high fine particulate matter (PM2.5) air pollution but has sparse regulatory air monitoring. Challenges for low-cost PM2.5 sensors in India include high-aerosol mass concentrations and pronounced regional and seasonal gradients in aerosol composition. Here, we report on a detailed long-time performance evaluation of a popular sensor, the Purple Air PA-II, at multiple sites in India.