Dr. P. Georgopoulos has developed machine learning based, transport/fate and climate models to characterize climate driven wildfire exposures in regional scale, but also to quantify accurately their contribution to global warming. Similarly, Dr. Kelesidis recently showed that incorporating accurate black carbon optical properties in climate models is essential for the accurate estimation of its radiative forcing and climate change impact, explaining satellite observations and climate change.

Climate change is increasingly recognized as a global health threat to humans, including female reproduction. Under the supports from NIH and New Jersey Department of Environmental Health Protection (NJDEP), Dr. Shuo Xiao and his team use both classic whole animal model and the emerging organ-a-chip model to study the impact exposure to climate change-related environmental contaminants and other stressors (e.g., extreme heat) on women’s sex hormone secretion, ovulation, and fertility as well as the toxic mechanisms involved. The toxicants they focus on include harmful algal bloom (HAB) toxins, wildfire smoke, and mycotoxins. Dr. Xiao and Lauren Aleksunes also recently received a Seed Fund from the Rutgers Office of Research to study how HAB toxins accumulate in the placenta in pregnant women and the potential developmental toxicities. These studies are important for us to develop mechanism-based strategies to prevent, mitigate, and remediate climate change-induced defective female reproductive health.