China faces well known air quality problems, which will likely have profound population health effects. At a fundamental level, there is not yet agreement on clinically significant pollution exposure levels, the relative important of exposure durations or the interactive effects of multiple pollutants together. There is also little rigorous evidence on the basic functional form of the multidimensional pollution-mortality relationship.
This project will build an unprecedented disaggregated dataset matching four years of hourly pollutant measurements with daily age-specific mortality rates in each of 278 cities in China. The researchers will use innovative machine learning tools to develop a data-driven empirical approach that provides new evidence on these major research questions. They will also engage with key policymakers to disseminate the findings.
Grant Miller (Medicine, SIEPR)
Lynn Hildemann (Civil and Environmental Engineering)
Hongbin Li (SIEPR)