Air pollution lAB
Connecting science to air quality decision-making
Connecting science to air quality decision-making
Environmental data science and artificial intelligence (AI)
Research Aims:
- Mitigate air pollution exposures, health outcomes, and inequities
- Investigate the impacts of climate change on air quality
Research Approaches:
- Multi-tiered observations of air pollution including criteria air pollutants and greenhouse gases
- Data analytics using statistics, machine learning, and geographic information systems (GIS)
- Data-driven conclusions to inform policies and regulations on air quality and carbon neutrality
