Health benefits of air pollution mitigation: A comparative assessment of policies for high (India) and low (Australia) exposure regions
About this project
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:
Improving the ambient PM2.5 exposure estimates by integrating in-situ, satellite and chemical transport model (CTM) based outputs in a machine learning environment at typical urban scales.
Improving the health burden estimates of ambient PM2.5 exposure by integrating exposure estimates and local health data in each country.
Understanding the expected health benefits from various realistic policies that are being implemented or planned for implementation to curb air pollution.
A comparative assessment of different policy scenarios in India (high exposure region) and Australia (low exposure region).
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.
Best possible PM2.5 exposure database for India and Australia.
Comparative assessment of burden between Indian and Australian cities, including the role of socio-economic and demographic differences in influencing the air pollution impacts.
Evaluation of the policies (in terms of the effectiveness).
Strategic knowledge to improve air quality management in India and Australia through improved exposure data at city through to regional scale, improved frameworks to assess the policies and improved understanding of the changing nature of air pollution in dynamic urban regions.
Information for applicants
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.
Expected qualifications (Course/Degrees etc.)
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.