Air pollution is the leading environmental cause of mortality and morbidity in the world. Despite significant progress in air pollution epidemiology, uncertainty in estimating the burden remains large, especially in data poor countries like India. Moreover, whether the relative burden of PM2.5 exposure is similar in high exposure regions (like India, where annual average PM2.5 is >70 µg/m3) and low exposure regions (like Australia where annual average PM2.5 is <10 µg/m3) is not known.
This project involves the following key objectives:
Combining the strengths of in-situ, satellite and CTMs, continuous PM2.5 exposure data at highly resolved spatial and time scales will be a key part of this project. The short and long-term impacts of air pollution in Indian and Australian cities will be examined using local health data. Several policies are implemented in Delhi NCR to curb air pollution. In this project, the potential health benefits of such policies will be evaluated and compared with other possible mitigation scenarios.
Experience in analysis of remote sensing data and/or climate modelling and computing skills (in Matlab and/or R and/or Python).
Background in this field with essential experience and prior work experience in air pollution research, particularly air pollution measurement. Experience working with large health data sets and/or epidemiological studies is highly desirable.
M.Tech/Msc (with GATE/NET/DST-INSPIRE) in a relevant discipline (atmospheric science, epidemiology, biotechnology, environmental science, public health, statistics and/or biostatistics).
Atmospheric Science, Environmental Science, Public Health, Biostatistics.