Unraveling Biological Pathways and Health Impacts of Air Pollution Components to Inform Climate Mitigation
Year of award: 2025
Grantholders
Dr Mary Rice
Harvard T.H. Chan School of Public Health, United States
Dr Jin-Ah Park
Harvard T.H. Chan School of Public Health, United States
Prof Joel Schwartz
Harvard T.H. Chan School of Public Health, United States
Dr Antonella Zanobetti
Harvard T.H. Chan School of Public Health, United States
Amruta Nori-Sarma
Harvard T.H. Chan School of Public Health, United States
Project summary
This research program addresses the urgent need to quantify dose-response relationships of real-world air pollution exposures on biology to inform climate mitigation. It directly tackles critical research gaps: understanding cumulative and combined pollutant exposures and identifying critical exposure thresholds for adverse health effects. The program is structured around two integrated projects. Project 1 (Mechanistic Studies) will characterize source-specific PM2.5 from urban hotspots to define their toxicological profiles and disease pathways in 3D human airway models. This includes assessing susceptibility in diseased airway cells (asthma, COPD) and investigating systemic links to cancer, immune dysregulation, and cardiovascular diseases. Project 2 (Population Studies) will develop high-resolution US air pollution models (PM2.5 components, NO2, O3) to link with nationwide health datasets (Medicaid, Medicare, HCUP). It will produce pollutant-, mixture-, and source-specific dose-response functions for respiratory, cardiovascular, neuropsychiatric, and cancer outcomes. This novel, integrated approach provides essential, policy-relevant evidence, including an interactive online tool to quantify potential health benefits of mitigation activities, enabling policymakers to effectively target hazardous pollutants and optimize public health outcomes. Keywords: Air pollution, PM2.5, climate change mitigation, health impacts, dose-response, cumulative exposures, pollutant mixtures, source apportionment, toxicological profiling, epidemiology, policy relevance, public health, computational modelling, environmental health.